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iPro70-FMWin: identifying Sigma70 promoters using multiple windowing and minimal features

Author:
Rahman, Md. Siddiqur, Aktar, Usma, Jani, Md Rafsan, Shatabda, Swakkhar
Source:
Molecular genetics and genomics 2019 v.294 no.1 pp. 69-84
ISSN:
1617-4615
Subject:
DNA, DNA-directed RNA polymerase, Internet, data collection, genome, nucleotides, prediction, promoter regions
Abstract:
In bacterial DNA, there are specific sequences of nucleotides called promoters that can bind to the RNA polymerase. Sigma70 ([Formula: see text]) is one of the most important promoter sequences due to its presence in most of the DNA regulatory functions. In this paper, we identify the most effective and optimal sequence-based features for prediction of [Formula: see text] promoter sequences in a bacterial genome. We used both short-range and long-range DNA sequences in our proposed method. A very small number of effective features are selected from a large number of the extracted features using multi-window of different sizes within the DNA sequences. We call our prediction method iPro70-FMWin and made it freely accessible online via a web application established at http://ipro70.pythonanywhere.com/server for the sake of convenience of the researchers. We have tested our method using a standard benchmark dataset. In the experiments, iPro70-FMWin has achieved an area under the curve of the receiver operating characteristic and accuracy of 0.959 and 90.57%, respectively, which significantly outperforms the state-of-the-art predictors.
Agid:
6299284