Literature DB >> 28186907

Identifying Sigma70 Promoters with Novel Pseudo Nucleotide Composition.

Hao Lin, Zhi-Yong Liang, Hua Tang, Wei Chen.   

Abstract

Promoters are DNA regulatory elements located directly upstream or at the 5' end of the transcription initiation site (TSS), which are in charge of gene transcription initiation. With the completion of a large number of microorganism genomics, it is urgent to predict promoters accurately in bacteria by using the computational method. In this work, a sequence-based predictor named "iPro70-PseZNC" was designed for identifying sigma70 promoters in prokaryote. In the predictor, the samples of DNA sequences are formulated by a novel pseudo nucleotide composition, called PseZNC, into which the multi-window Z-curve composition and six local DNA structural properties are incorporated. In the 5-fold cross-validation, the area under the curve of receiver operating characteristic of 0.909 was obtained on our benchmark dataset, indicating that the proposed predictor is promising and will provide an important guide in this area. Further studies showed that the performance of PseZNC is better than it of multi-window Z-curve composition. For the sake of convenience for researchers, a user-friendly online service was established and can be freely accessible at http://lin.uestc.edu.cn/server/iPro70-PseZNC. The PseZNC approach can be also extended to other DNA-related problems.

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Year:  2017        PMID: 28186907     DOI: 10.1109/TCBB.2017.2666141

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  42 in total

1.  PyFeat: a Python-based effective feature generation tool for DNA, RNA and protein sequences.

Authors:  Rafsanjani Muhammod; Sajid Ahmed; Dewan Md Farid; Swakkhar Shatabda; Alok Sharma; Abdollah Dehzangi
Journal:  Bioinformatics       Date:  2019-10-01       Impact factor: 6.937

2.  MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters.

Authors:  Meng Zhang; Fuyi Li; Tatiana T Marquez-Lago; André Leier; Cunshuo Fan; Chee Keong Kwoh; Kuo-Chen Chou; Jiangning Song; Cangzhi Jia
Journal:  Bioinformatics       Date:  2019-09-01       Impact factor: 6.937

3.  Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods.

Authors:  Fuyi Li; Yanan Wang; Chen Li; Tatiana T Marquez-Lago; André Leier; Neil D Rawlings; Gholamreza Haffari; Jerico Revote; Tatsuya Akutsu; Kuo-Chen Chou; Anthony W Purcell; Robert N Pike; Geoffrey I Webb; A Ian Smith; Trevor Lithgow; Roger J Daly; James C Whisstock; Jiangning Song
Journal:  Brief Bioinform       Date:  2019-11-27       Impact factor: 11.622

4.  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

5.  MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical descriptors.

Authors:  Robson P Bonidia; Douglas S Domingues; Danilo S Sanches; André C P L F de Carvalho
Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 11.622

6.  iPro-WAEL: a comprehensive and robust framework for identifying promoters in multiple species.

Authors:  Pengyu Zhang; Hongming Zhang; Hao Wu
Journal:  Nucleic Acids Res       Date:  2022-10-14       Impact factor: 19.160

7.  Application of unsupervised analysis techniques to lung cancer patient data.

Authors:  Chip M Lynch; Victor H van Berkel; Hermann B Frieboes
Journal:  PLoS One       Date:  2017-09-14       Impact factor: 3.240

8.  IonchanPred 2.0: A Tool to Predict Ion Channels and Their Types.

Authors:  Ya-Wei Zhao; Zhen-Dong Su; Wuritu Yang; Hao Lin; Wei Chen; Hua Tang
Journal:  Int J Mol Sci       Date:  2017-08-24       Impact factor: 5.923

9.  SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots.

Authors:  Irina S Moreira; Panagiotis I Koukos; Rita Melo; Jose G Almeida; Antonio J Preto; Joerg Schaarschmidt; Mikael Trellet; Zeynep H Gümüş; Joaquim Costa; Alexandre M J J Bonvin
Journal:  Sci Rep       Date:  2017-08-14       Impact factor: 4.379

10.  Multi-scale encoding of amino acid sequences for predicting protein interactions using gradient boosting decision tree.

Authors:  Chang Zhou; Hua Yu; Yijie Ding; Fei Guo; Xiu-Jun Gong
Journal:  PLoS One       Date:  2017-08-08       Impact factor: 3.240

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