PubAg

Main content area

Search

208  Search Results

« Previous | 1 - 100 of 208 |
Number of results to display per page

Search Results

1. A new correlation clustering method for cancer mutation analysis

Author:
Hou, Jack P.; Emad, Amin; Puleo, Gregory J.; Ma, Jian; Milenkovic, Olgica
Source:
Bioinformatics 2016 v.32 no.24 pp. 3717-3728
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; breast neoplasms; gene regulatory networks; genes; genomics; glioblastoma; graphs; mutation; mutational analysis; patients;     Show all 11 Subjects
Abstract:
... Motivation: Cancer genomes exhibit a large number of different alterations that affect many genes in a diverse manner. An improved understanding of the generative mechanisms behind the mutation rules and their influence on gene community behavior is of great importance for the study of cancer. Results: To expand our capability to analyze combinatorial patterns of cancer alterations, we developed a ...
DOI:
10.1093/bioinformatics/btw546

2. Fast-SNP: a fast matrix pre-processing algorithm for efficient loopless flux optimization of metabolic models

Author:
Saa, Pedro A.; Nielsen, Lars K.
Source:
Bioinformatics 2016 v.32 no.24 pp. 3807-3814
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; linear programming; models; thermodynamics; topology;     Show all 7 Subjects
Abstract:
... Motivation: Computation of steady-state flux solutions in large metabolic models is routinely performed using flux balance analysis based on a simple LP (Linear Programming) formulation. A minimal requirement for thermodynamic feasibility of the flux solution is the absence of internal loops, which are enforced using ‘loopless constraints’. The resulting loopless flux problem is a substantially ha ...
DOI:
10.1093/bioinformatics/btw555

3. H-PoP and H-PoPG: heuristic partitioning algorithms for single individual haplotyping of polyploids

Author:
Xie, Minzhu; Wu, Qiong; Wang, Jianxin; Jiang, Tao
Source:
Bioinformatics 2016 v.32 no.24 pp. 3735-3744
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; chromosomes; cotton; diploidy; dynamic programming; genome; haplotypes; high-throughput nucleotide sequencing; models; polyploidy; wheat;     Show all 12 Subjects
Abstract:
... Motivation: Some economically important plants including wheat and cotton have more than two copies of each chromosome. With the decreasing cost and increasing read length of next-generation sequencing technologies, reconstructing the multiple haplotypes of a polyploid genome from its sequence reads becomes practical. However, the computational challenge in polyploid haplotyping is much greater th ...
DOI:
10.1093/bioinformatics/btw537

4. ImmQuant: a user-friendly tool for inferring immune cell-type composition from gene-expression data

Author:
Frishberg, Amit; Brodt, Avital; Steuerman, Yael; Gat-Viks, Irit
Source:
Bioinformatics 2016 v.32 no.24 pp. 3842-3843
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; gene expression; humans; mice; tissues; transcriptome;     Show all 8 Subjects
Abstract:
... Summary: The composition of immune-cell subsets is key to the understanding of major diseases and pathologies. Computational deconvolution methods enable researchers to investigate immune cell quantities in complex tissues based on transcriptome data. Here we present ImmQuant, a software tool allowing immunologists to upload transcription profiles of multiple tissue samples, apply deconvolution me ...
DOI:
10.1093/bioinformatics/btw535

5. PhenomeScape: a cytoscape app to identify differentially regulated sub-networks using known disease associations

Author:
Soul, Jamie; Dunn, Sara L.; Hardingham, Tim E.; Boot-Handford, Ray P.; Schwartz, Jean-Marc
Source:
Bioinformatics 2016 v.32 no.24 pp. 3847-3849
ISSN:
1460-2059
Subject:
algorithms,   etc   ; animal models; bioinformatics; gene expression; gene expression regulation; genes; phenotype;     Show all 7 Subjects
Abstract:
... Summary: PhenomeScape is a Cytoscape app which provides easy access to the PhenomeExpress algorithm to interpret gene expression data. PhenomeExpress integrates protein interaction networks with known phenotype to gene associations to find active sub-networks enriched in differentially expressed genes. It also incorporates cross-species phenotypes and associations to include results from animal mo ...
DOI:
10.1093/bioinformatics/btw545

6. STAMS: STRING-assisted module search for genome wide association studies and application to autism

Author:
Hillenmeyer, Sara; Davis, Lea K.; Gamazon, Eric R.; Cook, Edwin H.; Cox, Nancy J.; Altman, Russ B.
Source:
Bioinformatics 2016 v.32 no.24 pp. 3815-3822
ISSN:
1460-2059
Subject:
algorithms,   etc   ; autism; bioinformatics; computer software; data collection; genes; genetic variation; genome-wide association study; insulin-dependent diabetes mellitus; phenotype; probability; rheumatoid arthritis;     Show all 12 Subjects
Abstract:
... Motivation: Analyzing genome wide association data in the context of biological pathways helps us understand how genetic variation influences phenotype and increases power to find associations. However, the utility of pathway-based analysis tools is hampered by undercuration and reliance on a distribution of signal across all of the genes in a pathway. Methods that combine genome wide association ...
DOI:
10.1093/bioinformatics/btw530

7. Bayesian network feature finder (BANFF): an R package for gene network feature selection

Author:
Lan, Zhou; Zhao, Yize; Kang, Jian; Yu, Tianwei
Source:
Bioinformatics 2016 v.32 no.23 pp. 3685-3687
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Bayesian theory; Markov chain; bioinformatics; computer software; gene expression; genes; models; protein-protein interactions;     Show all 9 Subjects
Abstract:
... Motivation: Network marker selection on genome-scale networks plays an important role in the understanding of biological mechanisms and disease pathologies. Recently, a Bayesian nonparametric mixture model has been developed and successfully applied for selecting genes and gene sub-networks. Hence, extending this method to a unified approach for network-based feature selection on general large-sca ...
DOI:
10.1093/bioinformatics/btw522

8. ChemTreeMap: an interactive map of biochemical similarity in molecular datasets

Author:
Lu, Jing; Carlson, Heather A.
Source:
Bioinformatics 2016 v.32 no.23 pp. 3584-3592
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioactive properties; bioinformatics; color; data collection; leaves; structure-activity relationships;     Show all 7 Subjects
Abstract:
... Motivation: What if you could explain complex chemistry in a simple tree and share that data online with your collaborators? Computational biology often incorporates diverse chemical data to probe a biological question, but the existing tools for chemical data are ill-suited for the very large datasets inherent to bioinformatics. Furthermore, existing visualization methods often require an expert ...
DOI:
10.1093/bioinformatics/btw523

9. DTMiner: identification of potential disease targets through biomedical literature mining

Author:
Xu, Dong; Zhang, Meizhuo; Xie, Yanping; Wang, Fan; Chen, Ming; Zhu, Kenny Q.; Wei, Jia
Source:
Bioinformatics 2016 v.32 no.23 pp. 3619-3626
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Internet; bioinformatics; data collection; genes;     Show all 5 Subjects
Abstract:
... Motivation: Biomedical researchers often search through massive catalogues of literature to look for potential relationships between genes and diseases. Given the rapid growth of biomedical literature, automatic relation extraction, a crucial technology in biomedical literature mining, has shown great potential to support research of gene-related diseases. Existing work in this field has produced ...
DOI:
10.1093/bioinformatics/btw503

10. LCA*: an entropy-based measure for taxonomic assignment within assembled metagenomes

Author:
Hanson, Niels W.; Konwar, Kishori M.; Hallam, Steven J.
Source:
Bioinformatics 2016 v.32 no.23 pp. 3535-3542
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; data collection; databases; entropy; genome; horizontal gene transfer; interspersed repetitive sequences; metagenomics; microorganisms; phylogeny; taxonomy;     Show all 12 Subjects
Abstract:
... Motivation: A perennial problem in the analysis of environmental sequence information is the assignment of reads or assembled sequences, e.g. contigs or scaffolds, to discrete taxonomic bins. In the absence of reference genomes for most environmental microorganisms, the use of intrinsic nucleotide patterns and phylogenetic anchors can improve assembly-dependent binning needed for more accurate tax ...
DOI:
10.1093/bioinformatics/btw400

11. SDEAP: a splice graph based differential transcript expression analysis tool for population data

Author:
Yang, Ei-Wen; Jiang, Tao
Source:
Bioinformatics 2016 v.32 no.23 pp. 3593-3602
ISSN:
1460-2059
Subject:
algorithms,   etc   ; alternative splicing; bioinformatics; biomarkers; cell cycle; exons; models; neoplasms; prediction; quantitative polymerase chain reaction; therapeutics; transcriptomics;     Show all 12 Subjects
Abstract:
... Motivation: Differential transcript expression (DTE) analysis without predefined conditions is critical to biological studies. For example, it can be used to discover biomarkers to classify cancer samples into previously unknown subtypes such that better diagnosis and therapy methods can be developed for the subtypes. Although several DTE tools for population data, i.e. data without known biologic ...
DOI:
10.1093/bioinformatics/btw513

12. SRinversion: a tool for detecting short inversions by splitting and re-aligning poorly mapped and unmapped sequencing reads

Author:
Chen, Ruoyan; Lau, Yu Lung; Zhang, Yan; Yang, Wanling
Source:
Bioinformatics 2016 v.32 no.23 pp. 3559-3565
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; data collection; databases; genetic variation; genome; humans;     Show all 7 Subjects
Abstract:
... Motivation: Rapid development in sequencing technologies has dramatically improved our ability to detect genetic variants in human genome. However, current methods have variable sensitivities in detecting different types of genetic variants. One type of such genetic variants that is especially hard to detect is inversions. Analysis of public databases showed that few short inversions have been rep ...
DOI:
10.1093/bioinformatics/btw516

13. LEVER: software tools for segmentation, tracking and lineaging of proliferating cells

Author:
Winter, Mark; Mankowski, Walter; Wait, Eric; Temple, Sally; Cohen, Andrew R.
Source:
Bioinformatics 2016 v.32 no.22 pp. 3530-3531
ISSN:
1460-2059
Subject:
algorithms,   etc   ; automation; bioinformatics; cell proliferation; clones; computer software; image analysis; neoplasm cells; neoplasms; phase-contrast microscopy; vertebrates;     Show all 11 Subjects
Abstract:
... The analysis of time-lapse images showing cells dividing to produce clones of related cells is an important application in biological microscopy. Imaging at the temporal resolution required to establish accurate tracking for vertebrate stem or cancer cells often requires the use of transmitted light or phase-contrast microscopy. Processing these images requires automated segmentation, tracking and ...
DOI:
10.1093/bioinformatics/btw406

14. NRGC: a novel referential genome compression algorithm

Author:
Saha, Subrata; Rajasekaran, Sanguthevar
Source:
Bioinformatics 2016 v.32 no.22 pp. 3405-3412
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Internet; bioinformatics; genome; high-throughput nucleotide sequencing; humans; nucleotide sequences;     Show all 7 Subjects
Abstract:
... Motivation: Next-generation sequencing techniques produce millions to billions of short reads. The procedure is not only very cost effective but also can be done in laboratory environment. The state-of-the-art sequence assemblers then construct the whole genomic sequence from these reads. Current cutting edge computing technology makes it possible to build genomic sequences from the billions of re ...
DOI:
10.1093/bioinformatics/btw505

15. ntHash: recursive nucleotide hashing

Author:
Mohamadi, Hamid; Chu, Justin; Vandervalk, Benjamin P.; Birol, Inanc
Source:
Bioinformatics 2016 v.32 no.22 pp. 3492-3494
ISSN:
1460-2059
Subject:
algorithms,   etc   ; DNA; RNA; bioinformatics; genome; nucleotide sequences; sequence alignment; transcriptome;     Show all 8 Subjects
Abstract:
... Motivation: Hashing has been widely used for indexing, querying and rapid similarity search in many bioinformatics applications, including sequence alignment, genome and transcriptome assembly, k-mer counting and error correction. Hence, expediting hashing operations would have a substantial impact in the field, making bioinformatics applications faster and more efficient. Results: We present ntHa ...
DOI:
10.1093/bioinformatics/btw397

16. PcircRNA_finder: a software for circRNA prediction in plants

Author:
Chen, Li; Yu, Yongyi; Zhang, Xinchen; Liu, Chen; Ye, Chuyu; Fan, Longjiang
Source:
Bioinformatics 2016 v.32 no.22 pp. 3528-3529
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Arabidopsis thaliana; bioinformatics; circular RNA; computer software; enzymes; genome; humans; prediction; rice; sequence analysis;     Show all 11 Subjects
Abstract:
... Motivation: Recent studies reveal an important role of non-coding circular RNA (circRNA) in the control of cellular processes. Because of differences in the organization of plant and mammal genomes, the sensitivity and accuracy of circRNA prediction programs using algorithms developed for animals and humans perform poorly for plants. Results: A circRNA prediction software for plants (termed PcircR ...
DOI:
10.1093/bioinformatics/btw496

17. plasmidSPAdes: assembling plasmids from whole genome sequencing data

Author:
Antipov, Dmitry; Hartwick, Nolan; Shen, Max; Raiko, Mikhail; Lapidus, Alla; Pevzner, Pavel A.
Source:
Bioinformatics 2016 v.32 no.22 pp. 3380-3387
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; chromosomes; computer software; genes; plasmids; sequence analysis; virulence;     Show all 8 Subjects
Abstract:
... Motivation: Plasmids are stably maintained extra-chromosomal genetic elements that replicate independently from the host cell’s chromosomes. Although plasmids harbor biomedically important genes, (such as genes involved in virulence and antibiotics resistance), there is a shortage of specialized software tools for extracting and assembling plasmid data from whole genome sequencing projects. Result ...
DOI:
10.1093/bioinformatics/btw493

18. sBWT: memory efficient implementation of the hardware-acceleration-friendly Schindler transform for the fast biological sequence mapping

Author:
Chang, Chia-Hua; Chou, Min-Te; Wu, Yi-Chung; Hong, Ting-Wei; Li, Yun-Lung; Yang, Chia-Hsiang; Hung, Jui-Hung
Source:
Bioinformatics 2016 v.32 no.22 pp. 3498-3500
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; genome;     Show all 4 Subjects
Abstract:
... Motivation: The Full-text index in Minute space (FM-index) derived from the Burrows–Wheeler transform (BWT) is broadly used for fast string matching in large genomes or a huge set of sequencing reads. Several graphic processing unit (GPU) accelerated aligners based on the FM-index have been proposed recently; however, the construction of the index is still handled by central processing unit (CPU), ...
DOI:
10.1093/bioinformatics/btw419

19. An empirical Bayes method for genotyping and SNP detection using multi-sample next-generation sequencing data

Author:
Huang, Gongyi; Wang, Shaoli; Wang, Xueqin; You, Na
Source:
Bioinformatics 2016 v.32 no.21 pp. 3240-3245
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; gene frequency; genetic variation; genotyping; high-throughput nucleotide sequencing; single nucleotide polymorphism; statistical models;     Show all 9 Subjects
Abstract:
... Motivation: The development of next generation sequencing technology provides an efficient and powerful approach to rare variant detection. To identify genetic variations, the essential question is how to quantity the sequencing error rate in the data. Because of the advantage of easy implementation and the ability to integrate data from different sources, the empirical Bayes method is popularly e ...
DOI:
10.1093/bioinformatics/btw409

20. ConsPred: a rule-based (re-)annotation framework for prokaryotic genomes

Author:
Weinmaier, Thomas; Platzer, Alexander; Frank, Jeroen; Hellinger, Hans-Jörg; Tischler, Patrick; Rattei, Thomas
Source:
Bioinformatics 2016 v.32 no.21 pp. 3327-3329
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; cloud computing; computer software; decision making; gene editing; genes; nucleotide sequences; prediction;     Show all 9 Subjects
Abstract:
... Motivation: The rapidly growing number of available prokaryotic genome sequences requires fully automated and high-quality software solutions for their initial and re-annotation. Here we present ConsPred, a prokaryotic genome annotation framework that performs intrinsic gene predictions, homology searches, predictions of non-coding genes as well as CRISPR repeats and integrates all evidence into a ...
DOI:
10.1093/bioinformatics/btw393

21. deBGA: read alignment with de Bruijn graph-based seed and extension

Author:
Liu, Bo; Guo, Hongzhe; Brudno, Michael; Wang, Yadong
Source:
Bioinformatics 2016 v.32 no.21 pp. 3224-3232
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; genome; high-throughput nucleotide sequencing;     Show all 4 Subjects
Abstract:
... Motivation: As high-throughput sequencing (HTS) technology becomes ubiquitous and the volume of data continues to rise, HTS read alignment is becoming increasingly rate-limiting, which keeps pressing the development of novel read alignment approaches. Moreover, promising novel applications of HTS technology require aligning reads to multiple genomes instead of a single reference; however, it is st ...
DOI:
10.1093/bioinformatics/btw371

22. LightAssembler: fast and memory-efficient assembly algorithm for high-throughput sequencing reads

Author:
El-Metwally, Sara; Zakaria, Magdi; Hamza, Taher
Source:
Bioinformatics 2016 v.32 no.21 pp. 3215-3223
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer hardware; computer techniques; data collection; genome; genomics; high-throughput nucleotide sequencing; mammals; statistical analysis;     Show all 10 Subjects
Abstract:
... Motivation: The deluge of current sequenced data has exceeded Moore’s Law, more than doubling every 2 years since the next-generation sequencing (NGS) technologies were invented. Accordingly, we will able to generate more and more data with high speed at fixed cost, but lack the computational resources to store, process and analyze it. With error prone high throughput NGS reads and genomic repeats ...
DOI:
10.1093/bioinformatics/btw470

23. MetaCycle: an integrated R package to evaluate periodicity in large scale data

Author:
Wu, Gang; Anafi, Ron C.; Hughes, Michael E.; Kornacker, Karl; Hogenesch, John B.
Source:
Bioinformatics 2016 v.32 no.21 pp. 3351-3353
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; data collection; periodicity; time series analysis;     Show all 6 Subjects
Abstract:
... Summary: Detecting periodicity in large scale data remains a challenge. While efforts have been made to identify best of breed algorithms, relatively little research has gone into integrating these methods in a generalizable method. Here, we present MetaCycle, an R package that incorporates ARSER, JTK_CYCLE and Lomb-Scargle to conveniently evaluate periodicity in time-series data. MetaCycle has tw ...
DOI:
10.1093/bioinformatics/btw405

24. Recognizing metal and acid radical ion-binding sites by integrating ab initio modeling with template-based transferals

Author:
Hu, Xiuzhen; Dong, Qiwen; Yang, Jianyi; Zhang, Yang
Source:
Bioinformatics 2016 v.32 no.21 pp. 3260-3269
ISSN:
1460-2059
Subject:
algorithms,   etc   ; binding sites; bioinformatics; calcium; carbonates; copper; databases; iron; ligands; magnesium; manganese; metal ions; models; nitrites; phosphates; potassium; prediction; proteins; sodium; sulfates; zinc;     Show all 21 Subjects
Abstract:
... Motivation: More than half of proteins require binding of metal and acid radical ions for their structure and function. Identification of the ion-binding locations is important for understanding the biological functions of proteins. Due to the small size and high versatility of the metal and acid radical ions, however, computational prediction of their binding sites remains difficult. Results: We ...
DOI:
10.1093/bioinformatics/btw396

25. The SMAL web server: global multiple network alignment from pairwise alignments

Author:
Dohrmann, Jakob; Singh, Rahul
Source:
Bioinformatics 2016 v.32 no.21 pp. 3330-3332
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Internet; bioinformatics; computer software; protein-protein interactions;     Show all 5 Subjects
Abstract:
... Motivation: Alignments of protein-protein interaction networks (PPIN) can be used to predict protein function, study conserved aspects of the interactome, and to establish evolutionary correspondences. Within this problem context, determining multiple network alignments (MNA) is a significant challenge that involves high computational complexity. A limited number of public MNA implementations are ...
DOI:
10.1093/bioinformatics/btw402

26. Unbiased classification of spatial strategies in the Barnes maze

Author:
Illouz, Tomer; Madar, Ravit; Clague, Charlotte; Griffioen, Kathleen J.; Louzoun, Yoram; Okun, Eitan
Source:
Bioinformatics 2016 v.32 no.21 pp. 3314-3320
ISSN:
1460-2059
Subject:
algorithms,   etc   ; automation; bioinformatics; cognition; memory; neurophysiology; rodents;     Show all 7 Subjects
Abstract:
... Motivation: Spatial learning is one of the most widely studied cognitive domains in neuroscience. The Morris water maze and the Barnes maze are the most commonly used techniques to assess spatial learning and memory in rodents. Despite the fact that these tasks are well-validated paradigms for testing spatial learning abilities, manual categorization of performance into behavioral strategies is su ...
DOI:
10.1093/bioinformatics/btw376

27. ACE: adaptive cluster expansion for maximum entropy graphical model inference

Author:
Barton, J. P.; De Leonardis, E.; Coucke, A.; Cocco, S.
Source:
Bioinformatics 2016 v.32 no.20 pp. 3089-3097
ISSN:
1460-2059
Subject:
algorithms,   etc   ; amino acid sequences; artificial intelligence; bioinformatics; data collection; prediction; probabilistic models; statistics;     Show all 8 Subjects
Abstract:
... Motivation: Graphical models are often employed to interpret patterns of correlations observed in data through a network of interactions between the variables. Recently, Ising/Potts models, also known as Markov random fields, have been productively applied to diverse problems in biology, including the prediction of structural contacts from protein sequence data and the description of neural activi ...
DOI:
10.1093/bioinformatics/btw328

28. pSumo-CD: predicting sumoylation sites in proteins with covariance discriminant algorithm by incorporating sequence-coupled effects into general PseAAC

Author:
Jia, Jianhua; Zhang, Liuxia; Liu, Zi; Xiao, Xuan; Chou, Kuo-Chen
Source:
Bioinformatics 2016 v.32 no.20 pp. 3133-3141
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Parkinson disease; amino acids; bioinformatics; chemical bonding; covariance; drugs; equations; genes; prediction; proteins; sumoylation;     Show all 12 Subjects
Abstract:
... Motivation: Sumoylation is a post-translational modification (PTM) process, in which small ubiquitin-related modifier (SUMO) is attaching by covalent bonds to substrate protein. It is critical to many different biological processes such as replicating genome, expressing gene, localizing and stabilizing proteins; unfortunately, it is also involved with many major disorders including Alzheimer’s and ...
DOI:
10.1093/bioinformatics/btw387

29. TADtool: visual parameter identification for TAD-calling algorithms

Author:
Kruse, Kai; Hug, Clemens B.; Hernández-Rodríguez, Benjamín; Vaquerizas, Juan M.
Source:
Bioinformatics 2016 v.32 no.20 pp. 3190-3192
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; genome;     Show all 4 Subjects
Abstract:
... Summary: Eukaryotic genomes are hierarchically organized into topologically associating domains (TADs). The computational identification of these domains and their associated properties critically depends on the choice of suitable parameters of TAD-calling algorithms. To reduce the element of trial-and-error in parameter selection, we have developed TADtool: an interactive plot to find robust TAD- ...
DOI:
10.1093/bioinformatics/btw368

30. AgIn: measuring the landscape of CpG methylation of individual repetitive elements

Author:
Suzuki, Yuta; Korlach, Jonas; Turner, Stephen W.; Tsukahara, Tatsuya; Taniguchi, Junko; Qu, Wei; Ichikawa, Kazuki; Yoshimura, Jun; Yurino, Hideaki; Takahashi, Yuji; Mitsui, Jun; Ishiura, Hiroyuki; Tsuji, Shoji; Takeda, Hiroyuki; Morishita, Shinichi
Source:
Bioinformatics 2016 v.32 no.19 pp. 2911-2919
ISSN:
1460-2059
Subject:
algorithms,   etc   ; DNA; DNA methylation; Oryzias latipes; bioinformatics; bisulfites; genome; humans; sequence analysis; transposons;     Show all 10 Subjects
Abstract:
... Motivation: Determining the methylation state of regions with high copy numbers is challenging for second-generation sequencing, because the read length is insufficient to map reads uniquely, especially when repetitive regions are long and nearly identical to each other. Single-molecule real-time (SMRT) sequencing is a promising method for observing such regions, because it is not vulnerable to GC ...
DOI:
10.1093/bioinformatics/btw360

31. Inferring the perturbation time from biological time course data

Author:
Yang, Jing; Penfold, Christopher A.; Grant, Murray R.; Rattray, Magnus
Source:
Bioinformatics 2016 v.32 no.19 pp. 2956-2964
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Arabidopsis; Bayesian theory; Pseudomonas syringae pv. tomato; bioinformatics; computer software; data collection; probabilistic models; probability; statistical analysis; transcription (genetics);     Show all 11 Subjects
Abstract:
... Motivation: Time course data are often used to study the changes to a biological process after perturbation. Statistical methods have been developed to determine whether such a perturbation induces changes over time, e.g. comparing a perturbed and unperturbed time course dataset to uncover differences. However, existing methods do not provide a principled statistical approach to identify the speci ...
DOI:
10.1093/bioinformatics/btw329

32. NegGOA: negative GO annotations selection using ontology structure

Author:
Fu, Guangyuan; Wang, Jun; Yang, Bo; Yu, Guoxian
Source:
Bioinformatics 2016 v.32 no.19 pp. 2996-3004
ISSN:
1460-2059
Subject:
algorithms,   etc   ; artificial intelligence; bioinformatics; computer software; gene ontology; humans; mice; models; prediction; proteins; yeasts;     Show all 11 Subjects
Abstract:
... Motivation: Predicting the biological functions of proteins is one of the key challenges in the post-genomic era. Computational models have demonstrated the utility of applying machine learning methods to predict protein function. Most prediction methods explicitly require a set of negative examples—proteins that are known not carrying out a particular function. However, Gene Ontology (GO) almost ...
DOI:
10.1093/bioinformatics/btw366

33. New KEGG pathway-based interpretable features for classifying ageing-related mouse proteins

Author:
Fabris, Fabio; Freitas, Alex A.
Source:
Bioinformatics 2016 v.32 no.19 pp. 2988-2995
ISSN:
1460-2059
Subject:
algorithms,   etc   ; artificial intelligence; bioinformatics; data collection; experts; genes; mice; models; phenotype; proteins;     Show all 10 Subjects
Abstract:
... Motivation: The incidence of ageing-related diseases has been constantly increasing in the last decades, raising the need for creating effective methods to analyze ageing-related protein data. These methods should have high predictive accuracy and be easily interpretable by ageing experts. To enable this, one needs interpretable classification models (supervised machine learning) and features with ...
DOI:
10.1093/bioinformatics/btw363

34. KCMBT: a k-mer Counter based on Multiple Burst Trees

Author:
Mamun, Abdullah-Al; Pal, Soumitra; Rajasekaran, Sanguthevar
Source:
Bioinformatics 2016 v.32 no.18 pp. 2783-2790
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; data collection; genome; genome assembly; humans; nucleotide sequences; sequence alignment;     Show all 8 Subjects
Abstract:
... Motivation: A massive number of bioinformatics applications require counting of k-length substrings in genetically important long strings. A k-mer counter generates the frequencies of each k-length substring in genome sequences. Genome assembly, repeat detection, multiple sequence alignment, error detection and many other related applications use a k-mer counter as a building block. Very fast and ...
DOI:
10.1093/bioinformatics/btw345

35. MetaFast: fast reference-free graph-based comparison of shotgun metagenomic data

Author:
Ulyantsev, Vladimir I.; Kazakov, Sergey V.; Dubinkina, Veronika B.; Tyakht, Alexander V.; Alexeev, Dmitry G.
Source:
Bioinformatics 2016 v.32 no.18 pp. 2760-2767
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; metagenomics; microbial communities; microorganisms; niches; nucleotide sequences; species diversity;     Show all 9 Subjects
Abstract:
... Motivation: High-throughput metagenomic sequencing has revolutionized our view on the structure and metabolic potential of microbial communities. However, analysis of metagenomic composition is often complicated by the high complexity of the community and the lack of related reference genomic sequences. As a start point for comparative metagenomic analysis, the researchers require efficient means ...
DOI:
10.1093/bioinformatics/btw312

36. pong: fast analysis and visualization of latent clusters in population genetic data

Author:
Behr, Aaron A.; Liu, Katherine Z.; Liu-Fang, Gracie; Nakka, Priyanka; Ramachandran, Sohini
Source:
Bioinformatics 2016 v.32 no.18 pp. 2817-2823
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; genome; genotype; human population; information retrieval; management systems; models; population genetics; population structure;     Show all 11 Subjects
Abstract:
... Motivation: A series of methods in population genetics use multilocus genotype data to assign individuals membership in latent clusters. These methods belong to a broad class of mixed-membership models, such as latent Dirichlet allocation used to analyze text corpora. Inference from mixed-membership models can produce different output matrices when repeatedly applied to the same inputs, and the nu ...
DOI:
10.1093/bioinformatics/btw327

37. Predicting regulatory variants with composite statistic

Author:
Li, Mulin Jun; Pan, Zhicheng; Liu, Zipeng; Wu, Jiexing; Wang, Panwen; Zhu, Yun; Xu, Feng; Xia, Zhengyuan; Sham, Pak Chung; Kocher, Jean-Pierre A.; Li, Miaoxin; Liu, Jun S.; Wang, Junwen
Source:
Bioinformatics 2016 v.32 no.18 pp. 2729-2736
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; data collection; genomics; humans; models; pathogenesis; pathogenicity; precision medicine; prediction; prioritization;     Show all 11 Subjects
Abstract:
... Motivation: Prediction and prioritization of human non-coding regulatory variants is critical for understanding the regulatory mechanisms of disease pathogenesis and promoting personalized medicine. Existing tools utilize functional genomics data and evolutionary information to evaluate the pathogenicity or regulatory functions of non-coding variants. However, different algorithms lead to inconsis ...
DOI:
10.1093/bioinformatics/btw288

38. RANKS: a flexible tool for node label ranking and classification in biological networks

Author:
Valentini, Giorgio; Armano, Giuliano; Frasca, Marco; Lin, Jianyi; Mesiti, Marco; Re, Matteo
Source:
Bioinformatics 2016 v.32 no.18 pp. 2872-2874
ISSN:
1460-2059
Subject:
algorithms,   etc   ; automation; bioinformatics; computer software; drugs; genes; prediction; prioritization;     Show all 8 Subjects
Abstract:
... Summary: RANKS is a flexible software package that can be easily applied to any bioinformatics task formalizable as ranking of nodes with respect to a property given as a label, such as automated protein function prediction, gene disease prioritization and drug repositioning. To this end RANKS provides an efficient and easy-to-use implementation of kernelized score functions, a semi-supervised alg ...
DOI:
10.1093/bioinformatics/btw235

39. Revealing aperiodic aspects of solenoid proteins from sequence information

Author:
Hrabe, Thomas; Jaroszewski, Lukasz; Godzik, Adam
Source:
Bioinformatics 2016 v.32 no.18 pp. 2776-2782
ISSN:
1460-2059
Subject:
algorithms,   etc   ; automation; bioinformatics; image analysis; leucine; processing technology; proteins;     Show all 7 Subjects
Abstract:
... Motivation: Repeat proteins, which contain multiple repeats of short sequence motifs, form a large but seldom-studied group of proteins. Methods focusing on the analysis of 3D structures of such proteins identified many subtle effects in length distribution of individual motifs that are important for their functions. However, similar analysis was yet not applied to the vast majority of repeat prot ...
DOI:
10.1093/bioinformatics/btw319

40. TarPmiR: a new approach for microRNA target site prediction

Author:
Ding, Jun; Li, Xiaoman; Hu, Haiyan
Source:
Bioinformatics 2016 v.32 no.18 pp. 2768-2775
ISSN:
1460-2059
Subject:
algorithms,   etc   ; artificial intelligence; bioinformatics; computational methodology; computer software; crosslinking; data collection; genes; humans; hybrids; mice; microRNA; prediction;     Show all 13 Subjects
Abstract:
... Motivation: The identification of microRNA (miRNA) target sites is fundamentally important for studying gene regulation. There are dozens of computational methods available for miRNA target site prediction. Despite their existence, we still cannot reliably identify miRNA target sites, partially due to our limited understanding of the characteristics of miRNA target sites. The recently published CL ...
DOI:
10.1093/bioinformatics/btw318

41. Top-down analysis of protein samples by de novo sequencing techniques

Author:
Vyatkina, Kira; Wu, Si; Dekker, Lennard J. M.; VanDuijn, Martijn M.; Liu, Xiaowen; Tolić, Nikola; Luider, Theo M.; Paša-Tolić, Ljiljana; Pevzner, Pavel A.
Source:
Bioinformatics 2016 v.32 no.18 pp. 2753-2759
ISSN:
1460-2059
Subject:
algorithms,   etc   ; amino acid sequences; amino acids; bioinformatics; post-translational modification; proteins; spectrometers; tandem mass spectrometry;     Show all 8 Subjects
Abstract:
... Motivation: Recent technological advances have made high-resolution mass spectrometers affordable to many laboratories, thus boosting rapid development of top-down mass spectrometry, and implying a need in efficient methods for analyzing this kind of data. Results: We describe a method for analysis of protein samples from top-down tandem mass spectrometry data, which capitalizes on de novo sequenc ...
DOI:
10.1093/bioinformatics/btw307

42. A probabilistic model for detecting rigid domains in protein structures

Author:
Nguyen, Thach; Habeck, Michael
Source:
Bioinformatics 2016 v.32 no.17 pp. i710
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Bayesian theory; Markov chain; automation; bioinformatics; databases; probabilistic models; protein structure; proteins;     Show all 9 Subjects
Abstract:
... Motivation : Large-scale conformational changes in proteins are implicated in many important biological functions. These structural transitions can often be rationalized in terms of relative movements of rigid domains. There is a need for objective and automated methods that identify rigid domains in sets of protein structures showing alternative conformational states. Results : We present a proba ...
DOI:
10.1093/bioinformatics/btw442

43. Bayesian parameter estimation for the Wnt pathway: an infinite mixture models approach

Author:
Koutroumpas, Konstantinos; Ballarini, Paolo; Votsi, Irene; Cournède, Paul-Henry
Source:
Bioinformatics 2016 v.32 no.17 pp. i781
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Bayesian theory; bioinformatics; computer software; mathematical models; signal transduction; statistical inference;     Show all 7 Subjects
Abstract:
... Motivation: Likelihood-free methods, like Approximate Bayesian Computation (ABC), have been extensively used in model-based statistical inference with intractable likelihood functions. When combined with Sequential Monte Carlo (SMC) algorithms they constitute a powerful approach for parameter estimation and model selection of mathematical models of complex biological systems. A crucial step in the ...
DOI:
10.1093/bioinformatics/btw471

44. Calculating and scoring high quality multiple flexible protein structure alignments

Author:
Ritchie, David W.
Source:
Bioinformatics 2016 v.32 no.17 pp. 2650-2658
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; data collection; models; protein structure;     Show all 5 Subjects
Abstract:
... Motivation: Calculating multiple protein structure alignments (MSAs) is important for understanding functional and evolutionary relationships between protein families, and for modeling protein structures by homology. While incorporating backbone flexibility promises to circumvent many of the limitations of rigid MSA algorithms, very few flexible MSA algorithms exist today. This article describes s ...
DOI:
10.1093/bioinformatics/btw300

45. CoLoRMap: Correcting Long Reads by Mapping short reads

Author:
Haghshenas, Ehsan; Hach, Faraz; Sahinalp, S. Cenk; Chauve, Cedric
Source:
Bioinformatics 2016 v.32 no.17 pp. i545
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bacteria; bioinformatics; data collection; fungi; genome; insects;     Show all 7 Subjects
Abstract:
... Motivation: Second generation sequencing technologies paved the way to an exceptional increase in the number of sequenced genomes, both prokaryotic and eukaryotic. However, short reads are difficult to assemble and often lead to highly fragmented assemblies. The recent developments in long reads sequencing methods offer a promising way to address this issue. However, so far long reads are characte ...
DOI:
10.1093/bioinformatics/btw463

46. Complementary feature selection from alternative splicing events and gene expression for phenotype prediction

Author:
Labuzzetta, Charles J.; Antonio, Margaret L.; Watson, Patricia M.; Wilson, Robert C.; Laboissonniere, Lauren A.; Trimarchi, Jeffrey M.; Genc, Baris; Ozdinler, P. Hande; Watson, Dennis K.; Anderson, Paul E.
Source:
Bioinformatics 2016 v.32 no.17 pp. i421
ISSN:
1460-2059
Subject:
algorithms,   etc   ; alternative splicing; amyotrophic lateral sclerosis; artificial intelligence; bioinformatics; biomarkers; data collection; engineering; gene expression; genes; humans; lung neoplasms; messenger RNA; mice; patients; phenotype; prediction; prioritization; sequence analysis; transgenic animals;     Show all 20 Subjects
Abstract:
... Motivation: A central task of bioinformatics is to develop sensitive and specific means of providing medical prognoses from biomarker patterns. Common methods to predict phenotypes in RNA-Seq datasets utilize machine learning algorithms trained via gene expression. Isoforms, however, generated from alternative splicing, may provide a novel and complementary set of transcripts for phenotype predict ...
DOI:
10.1093/bioinformatics/btw430

47. Confidence assignment for mass spectrometry based peptide identifications via the extreme value distribution

Author:
Alves, Gelio; Yu, Yi-Kuo
Source:
Bioinformatics 2016 v.32 no.17 pp. 2642-2649
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; databases; mass spectrometry; peptides; proteomics; statistics;     Show all 8 Subjects
Abstract:
... Motivation : There is a growing trend for biomedical researchers to extract evidence and draw conclusions from mass spectrometry based proteomics experiments, the cornerstone of which is peptide identification. Inaccurate assignments of peptide identification confidence thus may have far-reaching and adverse consequences. Although some peptide identification methods report accurate statistics, the ...
DOI:
10.1093/bioinformatics/btw225

48. densityCut: an efficient and versatile topological approach for automatic clustering of biological data

Author:
Ding, Jiarui; Shah, Sohrab; Condon, Anne
Source:
Bioinformatics 2016 v.32 no.17 pp. 2567-2576
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; cluster analysis; computer software; data collection; gene expression; information processing; microarray technology; neoplasms; somatic mutation; topology;     Show all 11 Subjects
Abstract:
... Motivation : Many biological data processing problems can be formalized as clustering problems to partition data points into sensible and biologically interpretable groups. Results : This article introduces densityCut, a novel density-based clustering algorithm, which is both time- and space-efficient and proceeds as follows: densityCut first roughly estimates the densities of data points from a K ...
DOI:
10.1093/bioinformatics/btw227

49. Drug repositioning based on comprehensive similarity measures and Bi-Random walk algorithm

Author:
Luo, Huimin; Wang, Jianxin; Li, Min; Luo, Junwei; Peng, Xiaoqing; Wu, Fang-Xiang; Pan, Yi
Source:
Bioinformatics 2016 v.32 no.17 pp. 2664-2671
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; case studies; chemical structure; data collection; drug development; drugs; phenotype; prediction;     Show all 9 Subjects
Abstract:
... Motivation: Drug repositioning, which aims to identify new indications for existing drugs, offers a promising alternative to reduce the total time and cost of traditional drug development. Many computational strategies for drug repositioning have been proposed, which are based on similarities among drugs and diseases. Current studies typically use either only drug-related properties (e.g. chemical ...
DOI:
10.1093/bioinformatics/btw228

50. Estimating real cell size distribution from cross-section microscopy imaging

Author:
Lenz, Michael; Roumans, Nadia J.T.; Vink, Roel G.; van Baak, Marleen A.; Mariman, Edwin C.M.; Arts, Ilja C.W.; de Kok, Theo M.; Ertaylan, Gökhan
Source:
Bioinformatics 2016 v.32 no.17 pp. i396
ISSN:
1460-2059
Subject:
algorithms,   etc   ; adipocytes; adipose tissue; bioinformatics; histology; image analysis; microscopy; molecular biology; nutritional intervention; people;     Show all 10 Subjects
Abstract:
... Motivation: Microscopy imaging is an essential tool for medical diagnosis and molecular biology. It is particularly useful for extracting information about disease states, tissue heterogeneity and cell specific parameters such as cell type or cell size from biological specimens. However, the information obtained from the images is likely to be subjected to sampling and observational bias with resp ...
DOI:
10.1093/bioinformatics/btw431

51. Fast genotyping of known SNPs through approximate k -mer matching

Author:
Shajii, Ariya; Yorukoglu, Deniz; William Yu, Yun; Berger, Bonnie
Source:
Bioinformatics 2016 v.32 no.17 pp. i538
ISSN:
1460-2059
Subject:
algorithms,   etc   ; alleles; bioinformatics; computer software; genetic traits; genomics; genotyping; high-throughput nucleotide sequencing; humans; loci; single nucleotide polymorphism;     Show all 11 Subjects
Abstract:
... Motivation: As the volume of next-generation sequencing (NGS) data increases, faster algorithms become necessary. Although speeding up individual components of a sequence analysis pipeline (e.g. read mapping) can reduce the computational cost of analysis, such approaches do not take full advantage of the particulars of a given problem. One problem of great interest, genotyping a known set of varia ...
DOI:
10.1093/bioinformatics/btw460

52. FastHiC: a fast and accurate algorithm to detect long-range chromosomal interactions from Hi-C data

Author:
Xu, Zheng; Zhang, Guosheng; Wu, Cong; Li, Yun; Hu, Ming
Source:
Bioinformatics 2016 v.32 no.17 pp. 2692-2695
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Bayesian theory; bioinformatics; chromatin; loci; probabilistic models; transcription (genetics);     Show all 7 Subjects
Abstract:
... Motivation: How chromatin folds in three-dimensional (3D) space is closely related to transcription regulation. As powerful tools to study such 3D chromatin conformation, the recently developed Hi-C technologies enable a genome-wide measurement of pair-wise chromatin interaction. However, methods for the detection of biologically meaningful chromatin interactions, i.e. peak calling, from Hi-C data ...
DOI:
10.1093/bioinformatics/btw240

53. Gene-set association tests for next-generation sequencing data

Author:
Lee, Jaehoon; Kim, Young Jin; Lee, Juyoung; ,; Kim, Bong-Jo; Lee, Seungyeoun; Park, Taesung
Source:
Bioinformatics 2016 v.32 no.17 pp. i611
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; enzymes; genes; high-throughput nucleotide sequencing; liver;     Show all 7 Subjects
Abstract:
... Motivation: Recently, many methods have been developed for conducting rare-variant association studies for sequencing data. These methods have primarily been based on gene-level associations but have not been proven to be as effective as expected. Gene-set-level tests have shown great advantages over gene-level tests in terms of power and robustness, because complex diseases are often caused by mu ...
DOI:
10.1093/bioinformatics/btw429

54. GTRAC: fast retrieval from compressed collections of genomic variants

Author:
Tatwawadi, Kedar; Hernaez, Mikel; Ochoa, Idoia; Weissman, Tsachy
Source:
Bioinformatics 2016 v.32 no.17 pp. i479
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Homo sapiens; bioinformatics; biomedical research; data collection; databases; genome; genomics; mathematical theory; nucleotide sequences;     Show all 10 Subjects
Abstract:
... Motivation : The dramatic decrease in the cost of sequencing has resulted in the generation of huge amounts of genomic data, as evidenced by projects such as the UK10K and the Million Veteran Project, with the number of sequenced genomes ranging in the order of 10 K to 1 M. Due to the large redundancies among genomic sequences of individuals from the same species, most of the medical research deal ...
DOI:
10.1093/bioinformatics/btw437

55. Information-optimal genome assembly via sparse read-overlap graphs

Author:
Shomorony, Ilan; Kim, Samuel H.; Courtade, Thomas A.; Tse, David N. C.
Source:
Bioinformatics 2016 v.32 no.17 pp. i494
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Escherichia coli K12; bioinformatics; data collection; genome; genome assembly; graphs;     Show all 7 Subjects
Abstract:
... Motivation : In the context of third-generation long-read sequencing technologies, read-overlap-based approaches are expected to play a central role in the assembly step. A fundamental challenge in assembling from a read-overlap graph is that the true sequence corresponds to a Hamiltonian path on the graph, and, under most formulations, the assembly problem becomes NP-hard, restricting practical a ...
DOI:
10.1093/bioinformatics/btw450

56. Large-scale inference of conjunctive Bayesian networks

Author:
Montazeri, Hesam; Kuipers, Jack; Kouyos, Roger; Böni, Jürg; Yerly, Sabine; Klimkait, Thomas; Aubert, Vincent; Günthard, Huldrych F.; Beerenwinkel, Niko
Source:
Bioinformatics 2016 v.32 no.17 pp. i727
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Bayesian theory; Human immunodeficiency virus; bioinformatics; cohort studies; computer software; data collection; databases; drug resistance; lamivudine; models; mutation; neoplasms; therapeutics;     Show all 14 Subjects
Abstract:
... The continuous time conjunctive Bayesian network (CT-CBN) is a graphical model for analyzing the waiting time process of the accumulation of genetic changes (mutations). CT-CBN models have been successfully used in several biological applications such as HIV drug resistance development and genetic progression of cancer. However, current approaches for parameter estimation and network structure lea ...
DOI:
10.1093/bioinformatics/btw459

57. ModuleAlign: module-based global alignment of protein–protein interaction networks

Author:
Hashemifar, Somaye; Ma, Jianzhu; Naveed, Hammad; Canzar, Stefan; Xu, Jinbo
Source:
Bioinformatics 2016 v.32 no.17 pp. i658
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; genes; humans; pathogenesis; pathogens; protein-protein interactions; proteins; topology;     Show all 9 Subjects
Abstract:
... Motivation: As an increasing amount of protein–protein interaction (PPI) data becomes available, their computational interpretation has become an important problem in bioinformatics. The alignment of PPI networks from different species provides valuable information about conserved subnetworks, evolutionary pathways and functional orthologs. Although several methods have been proposed for global ne ...
DOI:
10.1093/bioinformatics/btw447

58. OrfM: a fast open reading frame predictor for metagenomic data

Author:
Woodcroft, Ben J.; Boyd, Joel A.; Tyson, Gene W.
Source:
Bioinformatics 2016 v.32 no.17 pp. 2702-2703
ISSN:
1460-2059
Subject:
algorithms,   etc   ; DNA; bioinformatics; computer software; data collection; metagenomics; open reading frames; screening; stop codon; translation (genetics);     Show all 10 Subjects
Abstract:
... Summary: Finding and translating stretches of DNA lacking stop codons is a task common in the analysis of sequence data. However, the computational tools for finding open reading frames are sufficiently slow that they are becoming a bottleneck as the volume of sequence data grows. This computational bottleneck is especially problematic in metagenomics when searching unassembled reads, or screening ...
DOI:
10.1093/bioinformatics/btw241

59. PanTools: representation, storage and exploration of pan-genomic data

Author:
Sheikhizadeh, Siavash; Schranz, M. Eric; Akdel, Mehmet; de Ridder, Dick; Smit, Sandra
Source:
Bioinformatics 2016 v.32 no.17 pp. i487
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Arabidopsis thaliana; Escherichia coli; bioinformatics; computer software; data collection; databases; genes; genomics; high-throughput nucleotide sequencing; nucleotide sequences; yeasts;     Show all 12 Subjects
Abstract:
... Motivation: Next-generation sequencing technology is generating a wealth of highly similar genome sequences for many species, paving the way for a transition from single-genome to pan-genome analyses. Accordingly, genomics research is going to switch from reference-centric to pan-genomic approaches. We define the pan-genome as a comprehensive representation of multiple annotated genomes, facilitat ...
DOI:
10.1093/bioinformatics/btw455

60. PEPSI-Dock: a detailed data-driven protein–protein interaction potential accelerated by polar Fourier correlation

Author:
Neveu, Emilie; Ritchie, David W.; Popov, Petr; Grudinin, Sergei
Source:
Bioinformatics 2016 v.32 no.17 pp. i693
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Gibbs free energy; artificial intelligence; bioinformatics; models; prediction; protein structure; protein-protein interactions; proteins; sampling;     Show all 10 Subjects
Abstract:
... Motivation: Docking prediction algorithms aim to find the native conformation of a complex of proteins from knowledge of their unbound structures. They rely on a combination of sampling and scoring methods, adapted to different scales. Polynomial Expansion of Protein Structures and Interactions for Docking (PEPSI-Dock) improves the accuracy of the first stage of the docking pipeline, which will sh ...
DOI:
10.1093/bioinformatics/btw443

61. PRED-TMBB2: improved topology prediction and detection of beta-barrel outer membrane proteins

Author:
Tsirigos, Konstantinos D.; Elofsson, Arne; Bagos, Pantelis G.
Source:
Bioinformatics 2016 v.32 no.17 pp. i665
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Markov chain; amino acids; bioinformatics; data collection; models; outer membrane proteins; prediction; sequence alignment; topology; water solubility;     Show all 11 Subjects
Abstract:
... Motivation: The PRED-TMBB method is based on Hidden Markov Models and is capable of predicting the topology of beta-barrel outer membrane proteins and discriminate them from water-soluble ones. Here, we present an updated version of the method, PRED-TMBB2, with several newly developed features that improve its performance. The inclusion of a properly defined end state allows for better modeling of ...
DOI:
10.1093/bioinformatics/btw444

62. SA-SSR: a suffix array-based algorithm for exhaustive and efficient SSR discovery in large genetic sequences

Author:
Pickett, B. D.; Karlinsey, S. M.; Penrod, C. E.; Cormier, M. J.; Ebbert, M. T. W.; Shiozawa, D. K.; Whipple, C. J.; Ridge, P. G.
Source:
Bioinformatics 2016 v.32 no.17 pp. 2707-2709
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; forensic sciences; microsatellite repeats; phylogeny; population genetics;     Show all 7 Subjects
Abstract:
... Summary: Simple Sequence Repeats (SSRs) are used to address a variety of research questions in a variety of fields (e.g. population genetics, phylogenetics, forensics, etc.), due to their high mutability within and between species. Here, we present an innovative algorithm, SA-SSR, based on suffix and longest common prefix arrays for efficiently detecting SSRs in large sets of sequences. Existing S ...
DOI:
10.1093/bioinformatics/btw298

63. Simultaneous discovery of cancer subtypes and subtype features by molecular data integration

Author:
Le Van, Thanh; van Leeuwen, Matthijs; Carolina Fierro, Ana; De Maeyer, Dries; Van den Eynden, Jimmy; Verbeke, Lieven; De Raedt, Luc; Marchal, Kathleen; Nijssen, Siegfried
Source:
Bioinformatics 2016 v.32 no.17 pp. i445
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; breast neoplasms; carcinogenesis; models; prognosis;     Show all 6 Subjects
Abstract:
... Motivation: Subtyping cancer is key to an improved and more personalized prognosis/treatment. The increasing availability of tumor related molecular data provides the opportunity to identify molecular subtypes in a data-driven way. Molecular subtypes are defined as groups of samples that have a similar molecular mechanism at the origin of the carcinogenesis. The molecular mechanisms are reflected ...
DOI:
10.1093/bioinformatics/btw434

64. SWORD—a highly efficient protein database search

Author:
Vaser, Robert; Pavlović, Dario; Šikić, Mile
Source:
Bioinformatics 2016 v.32 no.17 pp. i680
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; data collection; databases;     Show all 4 Subjects
Abstract:
... Motivation: Protein database search is one of the fundamental problems in bioinformatics. For decades, it has been explored and solved using different exact and heuristic approaches. However, exponential growth of data in recent years has brought significant challenges in improving already existing algorithms. BLAST has been the most successful tool for protein database search, but is also becomin ...
DOI:
10.1093/bioinformatics/btw445

65. TOPDOM: database of conservatively located domains and motifs in proteins

Author:
Varga, Julia; Dobson, László; Tusnády, Gábor E.
Source:
Bioinformatics 2016 v.32 no.17 pp. 2725-2726
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Internet; bioinformatics; computer software; computers; databases; topology; transmembrane proteins; user interface;     Show all 9 Subjects
Abstract:
... Summary: The TOPDOM database—originally created as a collection of domains and motifs located consistently on the same side of the membranes in α-helical transmembrane proteins—has been updated and extended by taking into consideration consistently localized domains and motifs in globular proteins, too. By taking advantage of the recently developed CCTOP algorithm to determine the type of a protei ...
DOI:
10.1093/bioinformatics/btw193

66. flowAI: automatic and interactive anomaly discerning tools for flow cytometry data

Author:
Monaco, Gianni; Chen, Hao; Poidinger, Michael; Chen, Jinmiao; de Magalhães, João Pedro; Larbi, Anis
Source:
Bioinformatics 2016 v.32 no.16 pp. 2473-2480
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; flow cytometry; phenotype; user interface;     Show all 6 Subjects
Abstract:
... Motivation: Flow cytometry (FCM) is widely used in both clinical and basic research to characterize cell phenotypes and functions. The latest FCM instruments analyze up to 20 markers of individual cells, producing high-dimensional data. This requires the use of the latest clustering and dimensionality reduction techniques to automatically segregate cell sub-populations in an unbiased manner. Howev ...
DOI:
10.1093/bioinformatics/btw191

67. Memdock: an α-helical membrane protein docking algorithm

Author:
Hurwitz, Naama; Schneidman-Duhovny, Dina; Wolfson, Haim J.
Source:
Bioinformatics 2016 v.32 no.16 pp. 2444-2450
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; crystallization; databases; lipid bilayers; membrane proteins; nuclear magnetic resonance spectroscopy; protein structure;     Show all 8 Subjects
Abstract:
... Motivation: A wide range of fundamental biological processes are mediated by membrane proteins. Despite their large number and importance, less than 1% of all 3D protein structures deposited in the Protein Data Bank are of membrane proteins. This is mainly due to the challenges of crystallizing such proteins or performing NMR spectroscopy analyses. All the more so, there is only a small number of ...
DOI:
10.1093/bioinformatics/btw184

68. Muxstep: an open-source C ++ multiplex HMM library for making inferences on multiple data types

Author:
Veličković, Petar; Liò, Pietro
Source:
Bioinformatics 2016 v.32 no.16 pp. 2562-2564
ISSN:
1460-2059
Subject:
algorithms,   etc   ; artificial intelligence; bioinformatics; models; topology;     Show all 5 Subjects
Abstract:
... Motivation: With the development of experimental methods and technology, we are able to reliably gain access to data in larger quantities, dimensions and types. This has great potential for the improvement of machine learning (as the learning algorithms have access to a larger space of information). However, conventional machine learning approaches used thus far on single-dimensional data inputs a ...
DOI:
10.1093/bioinformatics/btw196

69. Partitioning and correlating subgroup characteristics from Aligned Pattern Clusters

Author:
Lee, En-Shiun Annie; Whelan, Fiona J.; Bowdish, Dawn M. E.; Wong, Andrew K. C.
Source:
Bioinformatics 2016 v.32 no.16 pp. 2427-2434
ISSN:
1460-2059
Subject:
algorithms,   etc   ; amino acids; bioinformatics; data collection; divergent evolution; functional properties; proteins; sequence homology;     Show all 8 Subjects
Abstract:
... Motivation: Evolutionarily conserved amino acids within proteins characterize functional or structural regions. Conversely, less conserved amino acids within these regions are generally areas of evolutionary divergence. A priori knowledge of biological function and species can help interpret the amino acid differences between sequences. However, this information is often erroneous or unavailable, ...
DOI:
10.1093/bioinformatics/btw211

70. ProtPOS: a python package for the prediction of protein preferred orientation on a surface

Author:
Ngai, Jimmy C. F.; Mak, Pui-In; Siu, Shirley W. I.
Source:
Bioinformatics 2016 v.32 no.16 pp. 2537-2538
ISSN:
1460-2059
Subject:
algorithms,   etc   ; adsorption; bioinformatics; computer software; energy; molecular dynamics; prediction;     Show all 7 Subjects
Abstract:
... Summary: Atomistic molecular dynamics simulation is a promising technique to investigate the energetics and dynamics in the protein–surface adsorption process which is of high relevance to modern biotechnological applications. To increase the chance of success in simulating the adsorption process, favorable orientations of the protein at the surface must be determined. Here, we present ProtPOS whi ...
DOI:
10.1093/bioinformatics/btw182

71. AlgoRun: a Docker-based packaging system for platform-agnostic implemented algorithms

Author:
Hosny, Abdelrahman; Vera-Licona, Paola; Laubenbacher, Reinhard; Favre, Thibauld
Source:
Bioinformatics 2016 v.32 no.15 pp. 2396-2398
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; user interface;     Show all 4 Subjects
Abstract:
... Motivation: There is a growing need in bioinformatics for easy-to-use software implementations of algorithms that are usable across platforms. At the same time, reproducibility of computational results is critical and often a challenge due to source code changes over time and dependencies. Results: The approach introduced in this paper addresses both of these needs with AlgoRun, a dedicated packag ...
DOI:
10.1093/bioinformatics/btw120

72. Analysis of CFSE time-series data using division-, age- and label-structured population models

Author:
Hross, Sabrina; Hasenauer, Jan
Source:
Bioinformatics 2016 v.32 no.15 pp. 2321-2329
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Bayesian theory; bioinformatics; cell proliferation; computational methodology; data collection; differential equation; dyes; models; system optimization; time series analysis; uncertainty; uncertainty analysis;     Show all 13 Subjects
Abstract:
... Motivation: In vitro and in vivo cell proliferation is often studied using the dye carboxyfluorescein succinimidyl ester (CFSE). The CFSE time-series data provide information about the proliferation history of populations of cells. While the experimental procedures are well established and widely used, the analysis of CFSE time-series data is still challenging. Many available analysis tools do not ...
DOI:
10.1093/bioinformatics/btw131

73. BLESS 2: accurate, memory-efficient and fast error correction method

Author:
Heo, Yun; Ramachandran, Anand; Hwu, Wen-Mei; Ma, Jian; Chen, Deming
Source:
Bioinformatics 2016 v.32 no.15 pp. 2369-2371
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; genome;     Show all 4 Subjects
Abstract:
... Summary: The most important features of error correction tools for sequencing data are accuracy, memory efficiency and fast runtime. The previous version of BLESS was highly memory-efficient and accurate, but it was too slow to handle reads from large genomes. We have developed a new version of BLESS to improve runtime and accuracy while maintaining a small memory usage. The new version, called BL ...
DOI:
10.1093/bioinformatics/btw146

74. ll-ACHRB: a scalable algorithm for sampling the feasible solution space of metabolic networks

Author:
Saa, Pedro A.; Nielsen, Lars K.
Source:
Bioinformatics 2016 v.32 no.15 pp. 2330-2337
ISSN:
1460-2059
Subject:
algorithms,   etc   ; biochemical pathways; bioinformatics; computer software; mixing; models; statistics; thermodynamics;     Show all 8 Subjects
Abstract:
... Motivation: Random sampling of the solution space has emerged as a popular tool to explore and infer properties of large metabolic networks. However, conventional sampling approaches commonly used do not eliminate thermodynamically unfeasible loops. Results: In order to overcome this limitation, we developed an efficient sampling algorithm called loopless Artificially Centered Hit-and-Run on a Box ...
DOI:
10.1093/bioinformatics/btw132

75. On genomic repeats and reproducibility

Author:
Firtina, Can; Alkan, Can
Source:
Bioinformatics 2016 v.32 no.15 pp. 2243-2247
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; data collection; genetic variation; genomics; high-throughput nucleotide sequencing;     Show all 6 Subjects
Abstract:
... Results: Here, we present a comprehensive analysis on the reproducibility of computational characterization of genomic variants using high throughput sequencing data. We reanalyzed the same datasets twice, using the same tools with the same parameters, where we only altered the order of reads in the input (i.e. FASTQ file). Reshuffling caused the reads from repetitive regions being mapped to diffe ...
DOI:
10.1093/bioinformatics/btw139

76. PinaColada: peptide–inhibitor ant colony ad-hoc design algorithm

Author:
Zaidman, Daniel; Wolfson, Haim J.
Source:
Bioinformatics 2016 v.32 no.15 pp. 2289-2296
ISSN:
1460-2059
Subject:
algorithms,   etc   ; amino acids; binding sites; bioinformatics; computers; drug design; peptides; protein-protein interactions; proteins; robots; system optimization;     Show all 11 Subjects
Abstract:
... Motivation: Design of protein–protein interaction (PPI) inhibitors is a major challenge in Structural Bioinformatics. Peptides, especially short ones (5–15 amino acid long), are natural candidates for inhibition of protein–protein complexes due to several attractive features such as high structural compatibility with the protein binding site (mimicking the surface of one of the proteins), small si ...
DOI:
10.1093/bioinformatics/btw133

77. Rapid genotype refinement for whole-genome sequencing data using multi-variate normal distributions

Author:
Arthur, Rudy; O’Connell, Jared; Schulz-Trieglaff, Ole; Cox, Anthony J.
Source:
Bioinformatics 2016 v.32 no.15 pp. 2306-2312
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Markov chain; bioinformatics; data collection; genotype; linkage disequilibrium; models; normal distribution; sequence analysis;     Show all 9 Subjects
Abstract:
... Motivation: Whole-genome low-coverage sequencing has been combined with linkage-disequilibrium (LD)-based genotype refinement to accurately and cost-effectively infer genotypes in large cohorts of individuals. Most genotype refinement methods are based on hidden Markov models, which are accurate but computationally expensive. We introduce an algorithm that models LD using a simple multivariate Gau ...
DOI:
10.1093/bioinformatics/btw097

78. APPAGATO: an APproximate PArallel and stochastic GrAph querying TOol for biological networks

Author:
Bonnici, Vincenzo; Busato, Federico; Micale, Giovanni; Bombieri, Nicola; Pulvirenti, Alfredo; Giugno, Rosalba
Source:
Bioinformatics 2016 v.32 no.14 pp. 2159-2166
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; case studies; computer software; gene ontology; protein-protein interactions; tissues; topology;     Show all 8 Subjects
Abstract:
... Motivation: Biological network querying is a problem requiring a considerable computational effort to be solved. Given a target and a query network, it aims to find occurrences of the query in the target by considering topological and node similarities (i.e. mismatches between nodes, edges, or node labels). Querying tools that deal with similarities are crucial in biological network analysis becau ...
DOI:
10.1093/bioinformatics/btw223

79. ARACNe-AP: gene network reverse engineering through adaptive partitioning inference of mutual information

Author:
Lachmann, Alexander; Giorgi, Federico M.; Lopez, Gonzalo; Califano, Andrea
Source:
Bioinformatics 2016 v.32 no.14 pp. 2233-2235
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; data collection; engineering; gene expression; gene regulatory networks; genes; probability distribution;     Show all 8 Subjects
Abstract:
... Summary: The accurate reconstruction of gene regulatory networks from large scale molecular profile datasets represents one of the grand challenges of Systems Biology. The Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) represents one of the most effective tools to accomplish this goal. However, the initial Fixed Bandwidth (FB) implementation is both inefficient and unable ...
DOI:
10.1093/bioinformatics/btw216

80. ASAFE: ancestry-specific allele frequency estimation

Author:
Zhang, Qian S.; Browning, Brian L.; Browning, Sharon R.
Source:
Bioinformatics 2016 v.32 no.14 pp. 2227-2229
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Hispanic Americans; ancestry; bioinformatics; gene frequency; genome-wide association study; genotype;     Show all 7 Subjects
Abstract:
... Summary: In a genome-wide association study (GWAS) of an admixed population, such as Hispanic Americans, ancestry-specific allele frequencies can inform the design of a replication GWAS. We derive an EM algorithm to estimate ancestry-specific allele frequencies for a bi-allelic marker given genotypes and local ancestries on a 3-way admixed population, when the phase of each admixed individual’s ge ...
DOI:
10.1093/bioinformatics/btw220

81. Characterizing gene sets using discriminative random walks with restart on heterogeneous biological networks

Author:
Blatti, Charles; Sinha, Saurabh
Source:
Bioinformatics 2016 v.32 no.14 pp. 2167-2175
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Drosophila; animals; binding sites; bioinformatics; brain; computer software; embryogenesis; genes; transcription factors;     Show all 10 Subjects
Abstract:
... Motivation: Analysis of co-expressed gene sets typically involves testing for enrichment of different annotations or ‘properties’ such as biological processes, pathways, transcription factor binding sites, etc., one property at a time. This common approach ignores any known relationships among the properties or the genes themselves. It is believed that known biological relationships among genes an ...
DOI:
10.1093/bioinformatics/btw151

82. gkmSVM: an R package for gapped-kmer SVM

Author:
Ghandi, Mahmoud; Mohammad-Noori, Morteza; Ghareghani, Narges; Lee, Dongwon; Garraway, Levi; Beer, Michael A.
Source:
Bioinformatics 2016 v.32 no.14 pp. 2205-2207
ISSN:
1460-2059
Subject:
algorithms,   etc   ; DNA; amino acid sequences; bioinformatics; computer software; nucleotide sequences;     Show all 6 Subjects
Abstract:
... Summary: We present a new R package for training gapped-kmer SVM classifiers for DNA and protein sequences. We describe an improved algorithm for kernel matrix calculation that speeds run time by about 2 to 5-fold over our original gkmSVM algorithm. This package supports several sequence kernels, including: gkmSVM, kmer-SVM, mismatch kernel and wildcard kernel. Availability and Implementation: gkm ...
DOI:
10.1093/bioinformatics/btw203

83. Incorporating organelle correlations into semi-supervised learning for protein subcellular localization prediction

Author:
Xu, Ying-Ying; Yang, Fan; Shen, Hong-Bin
Source:
Bioinformatics 2016 v.32 no.14 pp. 2184-2192
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Bayesian theory; artificial intelligence; automation; bioinformatics; data collection; fluorescent antibody technique; immunohistochemistry; organelles; prediction; proteins; topology;     Show all 12 Subjects
Abstract:
... Motivation: Bioimages of subcellular protein distribution as a new data source have attracted much attention in the field of automated prediction of proteins subcellular localization. Performance of existing systems is significantly limited by the small number of high-quality images with explicit annotations, resulting in the small sample size learning problem. This limitation is more serious for ...
DOI:
10.1093/bioinformatics/btw219

84. MOLGENIS/connect: a system for semi-automatic integration of heterogeneous phenotype data with applications in biobanks

Author:
Pang, Chao; van Enckevort, David; de Haan, Mark; Kelpin, Fleur; Jetten, Jonathan; Hendriksen, Dennis; de Boer, Tommy; Charbon, Bart; Winder, Erwin; van der Velde, K. Joeri; Doiron, Dany; Fortier, Isabel; Hillege, Hans; Swertz, Morris A.
Source:
Bioinformatics 2016 v.32 no.14 pp. 2176-2183
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; body mass index; data collection; humans; patients; phenotype; terminology;     Show all 8 Subjects
Abstract:
... Motivation: While the size and number of biobanks, patient registries and other data collections are increasing, biomedical researchers still often need to pool data for statistical power, a task that requires time-intensive retrospective integration. Results: To address this challenge, we developed MOLGENIS/connect, a semi-automatic system to find, match and pool data from different sources. The ...
DOI:
10.1093/bioinformatics/btw155

85. Spectral identification of topological domains

Author:
Chen, Jie; Hero, Alfred O.; Rajapakse, Indika
Source:
Bioinformatics 2016 v.32 no.14 pp. 2151-2158
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; genes; interphase; loci; topology; transcription (genetics);     Show all 8 Subjects
Abstract:
... Motivation: Topological domains have been proposed as the backbone of interphase chromosome structure. They are regions of high local contact frequency separated by sharp boundaries. Genes within a domain often have correlated transcription. In this paper, we present a computational efficient spectral algorithm to identify topological domains from chromosome conformation data (Hi-C data). We consi ...
DOI:
10.1093/bioinformatics/btw221

86. An algorithm for designing minimal microbial communities with desired metabolic capacities

Author:
Eng, Alexander; Borenstein, Elhanan
Source:
Bioinformatics 2016 v.32 no.13 pp. 2008-2016
ISSN:
1460-2059
Subject:
algorithms,   etc   ; biochemical pathways; bioinformatics; bioreactors; engineering; industrial applications; intestinal microorganisms; linear programming; metabolites; microbial communities;     Show all 10 Subjects
Abstract:
... Motivation: Recent efforts to manipulate various microbial communities, such as fecal microbiota transplant and bioreactor systems’ optimization, suggest a promising route for microbial community engineering with numerous medical, environmental and industrial applications. However, such applications are currently restricted in scale and often rely on mimicking or enhancing natural communities, cal ...
DOI:
10.1093/bioinformatics/btw107

87. Detection and removal of spatial bias in multiwell assays

Author:
Lachmann, Alexander; Giorgi, Federico M.; Alvarez, Mariano J.; Califano, Andrea
Source:
Bioinformatics 2016 v.32 no.13 pp. 1959-1965
ISSN:
1460-2059
Subject:
algorithms,   etc   ; autocorrelation; automation; bioinformatics; data collection; gene expression; principal component analysis;     Show all 7 Subjects
Abstract:
... Motivation: Multiplex readout assays are now increasingly being performed using microfluidic automation in multiwell format. For instance, the Library of Integrated Network-based Cellular Signatures (LINCS) has produced gene expression measurements for tens of thousands of distinct cell perturbations using a 384-well plate format. This dataset is by far the largest 384-well gene expression measure ...
DOI:
10.1093/bioinformatics/btw092

88. Direct calculation of minimal cut sets involving a specific reaction knock-out

Author:
Tobalina, Luis; Pey, Jon; Planes, Francisco J.
Source:
Bioinformatics 2016 v.32 no.13 pp. 2001-2007
ISSN:
1460-2059
Subject:
algorithms,   etc   ; biochemical pathways; bioinformatics; genes; models;     Show all 5 Subjects
Abstract:
... Motivation: The concept of Minimal Cut Sets (MCSs) is used in metabolic network modeling to describe minimal groups of reactions or genes whose simultaneous deletion eliminates the capability of the network to perform a specific task. Previous work showed that MCSs where closely related to Elementary Flux Modes (EFMs) in a particular dual problem, opening up the possibility to use the tools develo ...
DOI:
10.1093/bioinformatics/btw072

89. ecceTERA: comprehensive gene tree-species tree reconciliation using parsimony

Author:
Jacox, Edwin; Chauve, Cedric; Szöllősi, Gergely J.; Ponty, Yann; Scornavacca, Celine
Source:
Bioinformatics 2016 v.32 no.13 pp. 2056-2058
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; gene duplication; genes; models; phylogeny;     Show all 6 Subjects
Abstract:
... Summary: A gene tree-species tree reconciliation explains the evolution of a gene tree within the species tree given a model of gene-family evolution. We describe ecceTERA, a program that implements a generic parsimony reconciliation algorithm, which accounts for gene duplication, loss and transfer (DTL) as well as speciation, involving sampled and unsampled lineages, within undated, fully dated o ...
DOI:
10.1093/bioinformatics/btw105

90. IsomiR Bank: a research resource for tracking IsomiRs

Author:
Zhang, Yuanwei; Zang, Qiguang; Xu, Bo; Zheng, Wei; Ban, Rongjun; Zhang, Huan; Yang, Yifan; Hao, Qiaomei; Iqbal, Furhan; Li, Ao; Shi, Qinghua
Source:
Bioinformatics 2016 v.32 no.13 pp. 2069-2071
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Arabidopsis thaliana; Danio rerio; Drosophila melanogaster; Homo sapiens; Mus musculus; Oryza sativa; Solanum lycopersicum; Zea mays; bioinformatics; databases; high-throughput nucleotide sequencing; microRNA; prediction;     Show all 14 Subjects
Abstract:
... Summary: Next-Generation Sequencing (NGS) technology has revealed that microRNAs (miRNAs) are capable of exhibiting frequent differences from their corresponding mature reference sequences, generating multiple variants: the isoforms of miRNAs (isomiRs). These isomiRs mainly originate via the imprecise and alternative cleavage during the pre-miRNA processing and post-transcriptional modifications t ...
DOI:
10.1093/bioinformatics/btw070

91. metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

Author:
Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J.; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T.; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti
Source:
Bioinformatics 2016 v.32 no.13 pp. 1981-1989
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; covariance; genes; genome-wide association study; genotype; genotype-phenotype correlation; lipids; meta-analysis; metabolomics; multivariate analysis; nuclear magnetic resonance spectroscopy; phenotype;     Show all 13 Subjects
Abstract:
... Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level ...
DOI:
10.1093/bioinformatics/btw052

92. MetaKTSP: a meta-analytic top scoring pair method for robust cross-study validation of omics prediction analysis

Author:
Kim, SungHwan; Lin, Chien-Wei; Tseng, George. C.
Source:
Bioinformatics 2016 v.32 no.13 pp. 1966-1973
ISSN:
1460-2059
Subject:
algorithms,   etc   ; artificial intelligence; bioinformatics; biomarkers; breast neoplasms; computer software; data collection; fibrosis; genes; methylation; models; patients; prediction; prognosis; transcriptomics;     Show all 15 Subjects
Abstract:
... Motivation: Supervised machine learning is widely applied to transcriptomic data to predict disease diagnosis, prognosis or survival. Robust and interpretable classifiers with high accuracy are usually favored for their clinical and translational potential. The top scoring pair (TSP) algorithm is an example that applies a simple rank-based algorithm to identify rank-altered gene pairs for classifi ...
DOI:
10.1093/bioinformatics/btw115

93. Phasing for medical sequencing using rare variants and large haplotype reference panels

Author:
Sharp, Kevin; Kretzschmar, Warren; Delaneau, Olivier; Marchini, Jonathan
Source:
Bioinformatics 2016 v.32 no.13 pp. 1974-1980
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Markov chain; ancestry; bioinformatics; data collection; genetic variation; genome; haplotypes; humans;     Show all 9 Subjects
Abstract:
... Motivation: There is growing recognition that estimating haplotypes from high coverage sequencing of single samples in clinical settings is an important problem. At the same time very large datasets consisting of tens and hundreds of thousands of high-coverage sequenced samples will soon be available. We describe a method that takes advantage of these huge human genetic variation resources and rar ...
DOI:
10.1093/bioinformatics/btw065

94. repgenHMM: a dynamic programming tool to infer the rules of immune receptor generation from sequence data

Author:
Elhanati, Yuval; Marcou, Quentin; Mora, Thierry; Walczak, Aleksandra M.
Source:
Bioinformatics 2016 v.32 no.13 pp. 1943-1951
ISSN:
1460-2059
Subject:
algorithms,   etc   ; B-lymphocytes; Markov chain; T-lymphocytes; bioinformatics; computer software; dynamic programming; genes; humans; immunologic receptors; models; probability distribution;     Show all 12 Subjects
Abstract:
... Motivation: The diversity of the immune repertoire is initially generated by random rearrangements of the receptor gene during early T and B cell development. Rearrangement scenarios are composed of random events—choices of gene templates, base pair deletions and insertions—described by probability distributions. Not all scenarios are equally likely, and the same receptor sequence may be obtained ...
DOI:
10.1093/bioinformatics/btw112

95. RIPPER: a framework for MS1 only metabolomics and proteomics label-free relative quantification

Author:
Van Riper, Susan K.; Higgins, LeeAnn; Carlis, John V.; Griffin, Timothy J.
Source:
Bioinformatics 2016 v.32 no.13 pp. 2035-2037
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; mass spectrometry; metabolomics; proteomics;     Show all 6 Subjects
Abstract:
... Summary: RIPPER is a framework for mass-spectrometry-based label-free relative quantification for proteomics and metabolomics studies. RIPPER combines a series of previously described algorithms for pre-processing, analyte quantification, retention time alignment, and analyte grouping across runs. It is also the first software framework to implement proximity-based intensity normalization. RIPPER ...
DOI:
10.1093/bioinformatics/btw091

96. A cross-species bi-clustering approach to identifying conserved co-regulated genes

Author:
Sun, Jiangwen; Jiang, Zongliang; Tian, Xiuchun; Bi, Jinbo
Source:
Bioinformatics 2016 v.32 no.12 pp. i137
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; cluster analysis; computational methodology; computer software; data collection; developmental stages; embryo (animal); embryogenesis; gene expression; humans; mice; multigene family;     Show all 13 Subjects
Abstract:
... Motivation: A growing number of studies have explored the process of pre-implantation embryonic development of multiple mammalian species. However, the conservation and variation among different species in their developmental programming are poorly defined due to the lack of effective computational methods for detecting co-regularized genes that are conserved across species. The most sophisticated ...
DOI:
10.1093/bioinformatics/btw278

97. An algorithm for computing the gene tree probability under the multispecies coalescent and its application in the inference of population tree

Author:
Wu, Yufeng
Source:
Bioinformatics 2016 v.32 no.12 pp. i225
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; computer software; genes; haplotypes; models; phylogeny; probability; topology;     Show all 9 Subjects
Abstract:
... Motivation: Gene tree represents the evolutionary history of gene lineages that originate from multiple related populations. Under the multispecies coalescent model, lineages may coalesce outside the species (population) boundary. Given a species tree (with branch lengths), the gene tree probability is the probability of observing a specific gene tree topology under the multispecies coalescent mod ...
DOI:
10.1093/bioinformatics/btw261

98. A novel algorithm for calling mRNA m ⁶ A peaks by modeling biological variances in MeRIP-seq data

Author:
Cui, Xiaodong; Meng, Jia; Zhang, Shaowu; Chen, Yidong; Huang, Yufei
Source:
Bioinformatics 2016 v.32 no.12 pp. i378
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Markov chain; bioinformatics; data collection; messenger RNA; methylation; models; precipitin tests; prediction;     Show all 9 Subjects
Abstract:
... Motivation: N ⁶ -methyl-adenosine (m ⁶ A) is the most prevalent mRNA methylation but precise prediction of its mRNA location is important for understanding its function. A recent sequencing technology, known as Methylated RNA Immunoprecipitation Sequencing technology (MeRIP-seq), has been developed for transcriptome-wide profiling of m ⁶ A. We previously developed a peak calling algorithm called e ...
DOI:
10.1093/bioinformatics/btw281

99. BALL-SNPgp—from genetic variants toward computational diagnostics

Author:
Mueller, Sabine C.; Backes, Christina; Gress, Alexander; Baumgarten, Nina; Kalinina, Olga V.; Moll, Andreas; Kohlbacher, Oliver; Meese, Eckart; Keller, Andreas
Source:
Bioinformatics 2016 v.32 no.12 pp. 1888-1890
ISSN:
1460-2059
Subject:
algorithms,   etc   ; bioinformatics; biomedical research; cluster analysis; diabetes; diagnostic techniques; genetic variation; human diseases; neoplasms; pathogenicity;     Show all 10 Subjects
Abstract:
... Summary: In medical research, it is crucial to understand the functional consequences of genetic alterations, for example, non-synonymous single nucleotide variants (nsSNVs). NsSNVs are known to be causative for several human diseases. However, the genetic basis of complex disorders such as diabetes or cancer comprises multiple factors. Methods to analyze putative synergetic effects of multiple su ...
DOI:
10.1093/bioinformatics/btw084

100. Compacting de Bruijn graphs from sequencing data quickly and in low memory

Author:
Chikhi, Rayan; Limasset, Antoine; Medvedev, Paul
Source:
Bioinformatics 2016 v.32 no.12 pp. i201
ISSN:
1460-2059
Subject:
algorithms,   etc   ; Picea glauca; Pinus taeda; bioinformatics; data collection; graphs; humans;     Show all 7 Subjects
Abstract:
... Motivation : As the quantity of data per sequencing experiment increases, the challenges of fragment assembly are becoming increasingly computational. The de Bruijn graph is a widely used data structure in fragment assembly algorithms, used to represent the information from a set of reads. Compaction is an important data reduction step in most de Bruijn graph based algorithms where long simple pat ...
DOI:
10.1093/bioinformatics/btw279