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Computational Approaches for Transcription Factor Binding Prediction
by
Smitha C S,
Saritha R
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 94 - Number 11 |
| Year of Publication: 2014 |
| Authors: Smitha C S, Saritha R |
10.5120/16384-5969
|
Smitha C S, Saritha R . Computational Approaches for Transcription Factor Binding Prediction. International Journal of Computer Applications. 94, 11 ( May 2014), 1-5. DOI=10.5120/16384-5969
@article{
10.5120/16384-5969,
author = {
Smitha C S,
Saritha R
},
title = { Computational Approaches for Transcription Factor Binding Prediction },
journal = {
International Journal of Computer Applications
},
issue_date = { May 2014 },
volume = { 94 },
number = { 11 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = {
1-5
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume94/number11/16384-5969/
},
doi = { 10.5120/16384-5969 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:17:20.085331+05:30
%A Smitha C S
%A Saritha R
%T Computational Approaches for Transcription Factor Binding Prediction
%J International Journal of Computer Applications
%@ 0975-8887
%V 94
%N 11
%P 1-5
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The complexity of any organism depends on cellular behavior which is formed from the interaction between proteins and DNA. The accurate identification of DNA protein interaction is still a mirage. So computational approaches are used for the prediction of DNA protein interaction and the prediction results can be experimentally verified. In this paper a detailed survey of some of the prediction approaches in both prokaryotes and eukaryotes have been made. The prediction results may be useful for identification of putative binding sites.
References
- Patel S, Panchal H, Anjaria K, DNA Sequence Analysis by ORF FINDER & GENOMATIX tool: Bioinformatics Analysis of some Tree Species of Leguminosae Family, Bioinformatics and Biomedicine Workshop (BIBMW), IEEE International Confference 2012; doi:10. 1109/BIBMW. 2012. 6470265.
- Franco Zorrilla J M, Solano R, High Throughput Analysis of Protein-DNA Binding Affinity, Methods in Molecular Biology, NCBI PubMed 2014, 1062:697-709; doi:10. 1007/978-1- 62703-58-4 36.
- Timothy L Bailey and Philip Machanick, Inferring Direct DNA Binding from ChIP-Seq,Nucleic Acids Research 2012, doi: 10. 1093/nar/gks433.
- Lodish H, Berk A, Zipursky S L, Eukaryotic Transcription Activators and Repressors, Book:Molecular Cell Biology 2000.
- Anders Gorm Pedersen, Pierre Baldi, Yves Chauvin, Soren Brunak, The Biology of Eukaryotic Promoter Prediction - A Review, Computers and Chemistry 1991, 191-207, PERGAMON.
- Israa M. Al-Twaiki, Hassan Mathkur, Ameur Touir, M S Aksoy and Alaaeldin Hafez, Computational Approaches for Gene Prediction : A Comparative Survey, Sci. Int. (Lahore), 23(2), 83-90, 2001, ISSN:1013-5316.
- M Belfort, M E Reaban, T Coetzee and J Z Dalgaard, Prokaryotic Intons and Inteins : A Panoply of Form and Function,NCBI PMC177114 Journal of Bacteriology 1995, 3897-3903.
- Anthony Mathelier, Wyeth W Wasserman, The Next Generation of Transcription Factor Binding Site Prediction, PLOS Computational Biology 2013, doi:10. 1371/journal. pcbi. 1003214.
- Chen C Y, Morris Q, Mitchell J A, Enhancer Identification in Mouse Embryonic Stem Cells using Integrative Modeling of Chromatin and Genomic Features, BMC Genomics 2012, doi:10. 1186/1471-2164-13-152.
- Babu M M, Lucscombe N M, Aravind L, Gerstein M, Teichmann S A, Structure and Evolution of Transcriptional regulatory Network, PubMed 2004, 283-291.
- Tatsuhiko Tsunoda and Toshihisa Takgi, Estimating Transcription Factor Bindability on DNA, BIOINFORMATICS 1999, 622-630.
- A E Kel, E Go Bling, I Reuter, E Cheremushkin, O V Kel- Margoulis and E Wingender, MATCH, A Tool for Searching Transcription Factor Binding Sites in DNA Sequences, Nucleic Acids Research 2003, Vol. 31, No. 3.
- Modan K Das and Ho Kwok Dai, A survey of DNA Motif Finding Algorithms, BMC Bioinformatics 2007.
- Mark Maienschein Cline, Aaron R Dinner, William S Hlavacek, Fangping Mu Improved Predictions of Transcription Factor Binding Sites using Physicochemical Features of DNA, Nucleic Acids Research 2012.
- Julia V Ponomarenko, Dagmara P Furman, Antoly S Frolov, Nikolay L Podkolodny, Galina V Orlova, Mikhail P Ponomarenko, Nikolay A Kolchanov, Akinoi Sarai, ACTIVITY : A Database on DNA/RNA Sites Activity Adapted to Apply Sequence Activity Relationships from one System to Another, IEEE 2006.
- Alvaro Sebastian and Bruno Contreras-Moreira, footprintDB: a database of transcription factors with annotated cis elements and binding interfaces, Bioinformatics Advance Access, November, 2013.
- Swetlana Nikolajewa, Rainer Pudimat, Michael Hiller, Matthias Platzer, Rolf Backofen, BioBayesNet : A Web Server for Feature Extraction and Bayesian Network Modeling of Biological Sequence Data, Nucleic Acids Research 2007, PMC 1933181, doi:10. 1093/nar/qkm292.
- Liangjiang Wang, Mary Qu Yang and Jack Y Yang, Prediction of DNA-binding residues from protein sequence information using random forests, BMC Genomics 2009.
- Shandar Ahmed and Akinoi Sarai, PSSM based Prediction of DNA Binding Sites in Proteins, BMC Bioinformatics 2005.
- Colin R Lickwar, Florian Meuller, Sean E Hanlon, James G McNally, Jason D Lieb, Genome-wide proteinDNA binding dynamics suggest a molecular clutch for transcription factor function, Nature 484, 2012, 251-255, doi:10. 1038/nature10985.
- E Wingender, P Dietze, H Karas, R Knuppel, TRANSFAC : A Database on Transcription Factors and their DNA Binding Sites, Nucleic Acids Research 1996, Vol. 24, No: 1, 238-241.
- Dominique Vlieghe, Albin Sandelin, Rieter J De Bleser, Kris Vleminickx, Wyeth W Wasserman, Frans van Roy, Boris Lenhard, A New Generation of JASPAR, the Open Access Repository for Transcription Factor Binding Site Profiles, Nucleic Acids Research 2006 Vol 34, doi:10. 1093/nar/gkj115.
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