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81. 3DSpectra: A 3-dimensional quantification algorithm for LC–MS labeled profile data

Author:
Nasso, S.; Hartler, J.; Trajanoski, Z.; Di Camillo, B.; Mechtler, K.; Toffolo, G.M.
Source:
Journal of proteomics 2015 v.112 pp. 156-165
ISSN:
1874-3919
Subject:
normal distribution,   etc   ; algorithms; biomarkers; computer software; data collection; gene expression regulation; liquid chromatography; mass spectrometry; models; peptides; proteins; proteome; proteomics; surveys;     Show all 14 Subjects
Abstract:
... Mass spectrometry-based proteomics can generate highly informative datasets, as profile three-dimensional (3D) LC–MS data: LC–MS separates peptides in two dimensions (time, m/z) minimizing their overlap, and profile acquisition enhances quantification. To exploit both data features, we developed 3DSpectra, a 3D approach embedding a statistical method for peptide border recognition.3DSpectra effici ...
DOI:
10.1016/j.jprot.2014.08.017

82. Burned forest characterization at single-tree level with airborne laser scanning for assessing wildlife habitat

Author:
Casas, Ángeles; García, Mariano; Siegel, Rodney B.; Koltunov, Alexander; Ramírez, Carlos; Ustin, Susan
Source:
Remote sensing of environment 2016 v.175 pp. 231-241
ISSN:
0034-4257
Subject:
normal distribution,   etc   ; snags; trees; watersheds; remote sensing; woodpeckers; coniferous forests; wildlife habitats; woodlands; conifers; Picoides; equations; models; biodiversity; algorithms; wildlife; meadows; hardwood; allometry; regression analysis; environmental health; forest management; stand basal area; Sierra Nevada (California);     Show all 24 Subjects
Abstract:
... Abundance, size, and spatial distribution of standing dead trees (snags), are key indicators of forest biodiversity and ecosystem health. These metrics represent critical habitat components for various wildlife species of conservation concern, including the Black-backed Woodpecker (Picoides arcticus), which is strongly associated with recently burned conifer forest. We assessed the potential of Ai ...
DOI:
10.1016/j.rse.2015.12.044
Chorus Open Access:
10.1016/j.rse.2015.12.044

83. Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision

Author:
Pardo-Pascual, Josep E.; Almonacid-Caballer, Jaime; Ruiz, Luis A.; Palomar-Vázquez, Jesús
Source:
Remote sensing of environment 2012 v.123 pp. 1-11
ISSN:
0034-4257
Subject:
normal distribution,   etc   ; Landsat; algorithms; coasts; models; probability; reflectance; remote sensing; vegetation types;     Show all 9 Subjects
Abstract:
... A high precision geometric method for automated shoreline detection from Landsat TM and ETM+ imagery is presented. The methodology is based on the application of an algorithm that ensures accurate image geometric registration and the use of a new algorithm for sub-pixel shoreline extraction, both at the sub-pixel level. The analysis of the initial errors shows the influence that differences in ref ...
DOI:
10.1016/j.rse.2012.02.024

84. A novel partial least squares weighting Gaussian process algorithm and its application to near infrared spectroscopy data mining problems

Author:
Song, Kai; Tong, Tuopeng; Wu, Fang; Zhang, Ze
Source:
Analytical methods 2012 v.4 no.5 pp. 1395-1400
ISSN:
1759-9679
Subject:
normal distribution,   etc   ; algorithms; artificial intelligence; data collection; least squares; near-infrared spectroscopy;     Show all 6 Subjects
Abstract:
... A new partial least squares (PLS) weighting Gaussian process (PWGP) algorithm is proposed to improve the regression performance of Gaussian process (GP), an outstanding kernel-based machine learning method, on high dimensional data with small sample size, especially near-infrared (NIR) spectroscopy. Important indexes of original variables are firstly calculated according to their contributions to ...
DOI:
10.1039/c2ay25122a

85. Convergence rates and asymptotic standard errors for Markov chain Monte Carlo algorithms for Bayesian probit regression Series B Statistical methodology

Author:
Roy, Vivekananda; Hobert, James P.
Source:
Journal of the Royal Statistical Society 2007 v.69 no.4 pp. 607-623
ISSN:
1369-7412
Subject:
normal distribution,   etc   ; Markov chain; algorithms; variance;     Show all 4 Subjects
Abstract:
... Consider a probit regression problem in which Y₁, [ellipsis (horizontal)], Yn are independent Bernoulli random variables such that [graphic removed] where xi is a p-dimensional vector of known covariates that are associated with Yi, β is a p-dimensional vector of unknown regression coefficients and Φ(·) denotes the standard normal distribution function. We study Markov chain Monte Carlo algorithms ...
DOI:
10.1111/j.1467-9868.2007.00602.x

86. DegPack: A web package using a non-parametric and information theoretic algorithm to identify differentially expressed genes in multiclass RNA-seq samples

Author:
An, Jaehyun; Kim, Kwangsoo; Chae, Heejoon; Kim, Sun
Source:
Methods 2014 v.69 pp. 306-314
ISSN:
1046-2023
Subject:
normal distribution,   etc   ; Internet; algorithms; analysis of variance; breast neoplasms; data collection; drought tolerance; entropy; gene expression; gene expression regulation; microarray technology; phenotype; rice; sequence analysis; t-test;     Show all 15 Subjects
Abstract:
... Gene expression in the whole cell can be routinely measured by microarray technologies or recently by using sequencing technologies. Using these technologies, identifying differentially expressed genes (DEGs) among multiple phenotypes is the very first step to understand difference between phenotypes. Thus many methods for detecting DEGs between two groups have been developed. For example, T-test ...
DOI:
10.1016/j.ymeth.2014.06.004

87. Finite mixture models to characterize and refine air quality monitoring networks

Author:
Gómez-Losada, Álvaro; Lozano-García, Antonio; Pino-Mejías, Rafael; Contreras-González, Juan
Source:
The Science of the total environment 2014 v.485-486 pp. 292-299
ISSN:
0048-9697
Subject:
normal distribution,   etc   ; air; air quality; algorithms; carbon monoxide; cluster analysis; data collection; equipment; models; monitoring; nitrogen dioxide; ozone; particulates; pollutants; principal component analysis; source attribution; sulfur dioxide; Spain;     Show all 18 Subjects
Abstract:
... Existing air quality monitoring programs are, on occasion, not updated according to local, varying conditions and as such the monitoring programs become non-informative over time, under-detecting new sources of pollutants or duplicating information. Furthermore, inadequate maintenance may cause the monitoring equipment to be utterly deficient in providing information. To deal with these issues, a ...
DOI:
10.1016/j.scitotenv.2014.03.091

88. Gaussian processes retrieval of leaf parameters from a multi-species reflectance, absorbance and fluorescence dataset

Author:
Van Wittenberghe, Shari; Verrelst, Jochem; Rivera, Juan Pablo; Alonso, Luis; Moreno, José; Samson, Roeland
Source:
Journal of photochemistry and photobiology 2014 v.134 pp. 37-48
ISSN:
1011-1344
Subject:
normal distribution,   etc   ; absorbance; algorithms; artificial intelligence; chlorophyll; data collection; fluorescence; leaf area; leaves; models; nitrogen content; reflectance; regression analysis; water content; wavelengths;     Show all 15 Subjects
Abstract:
... Biochemical and structural leaf properties such as chlorophyll content (Chl), nitrogen content (N), leaf water content (LWC), and specific leaf area (SLA) have the benefit to be estimated through nondestructive spectral measurements. Current practices, however, mainly focus on a limited amount of wavelength bands while more information could be extracted from other wavelengths in the full range (4 ...
DOI:
10.1016/j.jphotobiol.2014.03.010

89. Optimal Operation of Discretely Controlled Continuous Systems under Uncertainty

Author:
De Paula, Mariano; Martínez, Ernesto C.
Source:
Industrial & Engineering Chemistry Research 2012 v.51 no.42 pp. 13743-13764
ISSN:
1520-5045
Subject:
normal distribution,   etc   ; algorithms; case studies; chemistry; continuous systems; dynamic programming; engineering; issues and policy; probabilistic models; uncertainty; utility functions;     Show all 11 Subjects
Abstract:
... Discretely controlled continuous systems constitute a special class of continuous-time hybrid dynamical systems where timely switching to alternative control modes is used for dynamic optimization in uncertain environments. Each mode implements a parametrized feedback control law until a stopping condition triggers due to the activation of a constraint related to states, controls, or disturbances. ...
DOI:
10.1021/ie301015z

90. Navigating the protein fitness landscape with Gaussian processes

Author:
Romero, Philip A.; Krause, Andreas; Arnold, Frances H.
Source:
Proceedings of the National Academy of Sciences of the United States of America 2013 v.110 no.3 pp. E193
ISSN:
0027-8424
Subject:
normal distribution,   etc   ; Bayesian theory; algorithms; binding capacity; chimerism; cytochrome P-450; directed evolution; engineering; enzyme activity; enzymes; landscapes; model uncertainty; models; thermal stability;     Show all 14 Subjects
Abstract:
... Knowing how protein sequence maps to function (the “fitness landscape”) is critical for understanding protein evolution as well as for engineering proteins with new and useful properties. We demonstrate that the protein fitness landscape can be inferred from experimental data, using Gaussian processes, a Bayesian learning technique. Gaussian process landscapes can model various protein sequence pr ...
DOI:
10.1073/pnas.1215251110
PubMed:
23277561
PubMed Central:
PMC3549130

91. Monthly streamflow forecasting using Gaussian Process Regression

Author:
Sun, Alexander Y.; Wang, Dingbao; Xu, Xianli
Source:
Journal of hydrology 2014 v.511 pp. 72-81
ISSN:
0022-1694
Subject:
normal distribution,   etc   ; algorithms; anthropogenic activities; artificial intelligence; basins; climate change; databases; human growth; hydrometeorology; linear models; neural networks; planning; prediction; regression analysis; stochastic processes; stream flow; sustainable development; time series analysis; water management; water resources; United States;     Show all 21 Subjects
Abstract:
... Streamflow forecasting plays a critical role in nearly all aspects of water resources planning and management. In this work, Gaussian Process Regression (GPR), an effective kernel-based machine learning algorithm, is applied to probabilistic streamflow forecasting. GPR is built on Gaussian process, which is a stochastic process that generalizes multivariate Gaussian distribution to infinite-dimens ...
DOI:
10.1016/j.jhydrol.2014.01.023

92. Protein Bioinformatics and Mixtures of Bivariate von Mises Distributions for Angular Data

Author:
Mardia, Kanti V.; Taylor, Charles C.; Subramaniam, Ganesh K.
Source:
Biometrics 2007 v.63 no.2 pp. 505-512
ISSN:
0006-341X
Subject:
normal distribution,   etc   ; algorithms; bioinformatics; biometry; data collection; models; protein secondary structure;     Show all 7 Subjects
Abstract:
... A fundamental problem in bioinformatics is to characterize the secondary structure of a protein, which has traditionally been carried out by examining a scatterplot (Ramachandran plot) of the conformational angles. We examine two natural bivariate von Mises distributions--referred to as Sine and Cosine models--which have five parameters and, for concentrated data, tend to a bivariate normal distri ...
DOI:
10.1111/j.1541-0420.2006.00682.x
PubMed:
17688502

93. Exploiting noise in array CGH data to improve detection of DNA copy number change

Author:
Hu, Jing; Gao, Jian-Bo; Cao, Yinhe; Bottinger, Erwin; Zhang, Weijia
Source:
Nucleic acids research 2007 v.35 no.5 pp. e35
ISSN:
0305-1048
Subject:
normal distribution,   etc   ; DNA; algorithms; bacterial artificial chromosomes; chromosome aberrations; methodology; neoplasms; pathogenesis;     Show all 8 Subjects
Abstract:
... Developing effective methods for analyzing array-CGH data to detect chromosomal aberrations is very important for the diagnosis of pathogenesis of cancer and other diseases. Current analysis methods, being largely based on smoothing and/or segmentation, are not quite capable of detecting both the aberration regions and the boundary break points very accurately. Furthermore, when evaluating the acc ...
DOI:
10.1093/nar/gkl730
PubMed:
17272296
PubMed Central:
PMC1994778

94. Impact of spatial variability of tropical forest structure on radar estimation of aboveground biomass

Author:
Saatchi, Sassan; Marlier, Miriam; Chazdon, Robin L.; Clark, David B.; Russell, Ann E.
Source:
Remote sensing of environment 2011 v.115 no.11 pp. 2836-2849
ISSN:
0034-4257
Subject:
normal distribution,   etc   ; aboveground biomass; algorithms; allometry; canopy gaps; confidence interval; correlation; equations; forest canopy; forest inventory; forest plantations; forest types; interferometry; landscapes; lidar; old-growth forests; polarimetry; radar; remote sensing; secondary succession; trees; tropical forests; Costa Rica;     Show all 23 Subjects
Abstract:
... Understanding the spatial variability of tropical forest structure and its impact on the radar estimation of aboveground biomass (AGB) is important to assess the scale and accuracy of mapping AGB with future low frequency radar missions. We used forest inventory plots in old growth, secondary succession, and forest plantations at the La Selva Biological Station in Costa Rica to examine the spatial ...
DOI:
10.1016/j.rse.2010.07.015

95. Evaluating Fibrous Architecture of Nonwovens with Computer-Assisted Microscopy 1

Author:
Krucinska, I.; Krucinski, S.
Source:
Textile research journal 1999 v.69 no.5 pp. 363-369
ISSN:
0040-5175
Subject:
normal distribution,   etc   ; algorithms; computers; image analysis; least squares; nonwoven fabrics; polarized light microscopy; silicon; textile fibers; video cameras;     Show all 10 Subjects
Abstract:
... A new computerized imaging, circular polarized light microscopy technique is de veloped to measure the orientation of fibers in images of nonwovens. The system consists of a modified Olympus BX50 polarized microscope, a Sony AVC-D7 video camera, and a Silicon Graphics Indy computer. There are two methods of image seg mentation : Gaussian distribution' based minimum error thresholding and Poisson d ...
DOI:
10.1177/004051759906900510