Literature DB >> 30187132

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

Md Siddiqur Rahman1, Usma Aktar1, Md Rafsan Jani1, Swakkhar Shatabda2.   

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.

Keywords:  Feature selection; Multi-windowing; Prokaryote; Sequence-based features; promoter

Mesh:

Substances:

Year:  2018        PMID: 30187132     DOI: 10.1007/s00438-018-1487-5

Source DB:  PubMed          Journal:  Mol Genet Genomics        ISSN: 1617-4623            Impact factor:   3.291


  4 in total

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Authors:  Nguyen Quoc Khanh Le
Journal:  Mol Genet Genomics       Date:  2019-05-04       Impact factor: 3.291

2.  Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction.

Authors:  Meng Zhang; Cangzhi Jia; Fuyi Li; Chen Li; Yan Zhu; Tatsuya Akutsu; Geoffrey I Webb; Quan Zou; Lachlan J M Coin; Jiangning Song
Journal:  Brief Bioinform       Date:  2022-03-10       Impact factor: 11.622

3.  Promotech: a general tool for bacterial promoter recognition.

Authors:  Ruben Chevez-Guardado; Lourdes Peña-Castillo
Journal:  Genome Biol       Date:  2021-11-17       Impact factor: 13.583

4.  PromoterLCNN: A Light CNN-Based Promoter Prediction and Classification Model.

Authors:  Daryl Hernández; Nicolás Jara; Mauricio Araya; Roberto E Durán; Carlos Buil-Aranda
Journal:  Genes (Basel)       Date:  2022-06-23       Impact factor: 4.141

  4 in total

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