Knowledge‐based three‐body potential for transcription factor binding site prediction-Reference-Cited by-同舟云学术

Knowledge‐based three‐body potential for transcription factor binding site prediction

Published:2016-02 Issue:1 Volume:10 Page:23-29
ISSN:1751-8849
Container-title:IET Systems Biology
language:en
Short-container-title:IET syst. biol.

Author:

Qin Wenyi¹²,Zhao Guijun¹³,Carson Matthew²,Jia Caiyan⁴,Lu Hui¹²

Affiliation:

1. Shanghai Institute of Medical Genetics, Shanghai Children's Hospital, Shanghai Jiaotong UniversityShanghaiPeople's Republic of China

2. Department of BioengineeringUniversity of Illinois at ChicagoChicagoILUSA

3. Key Laboratory of Molecular EmbryologyMinistry of Health & Shanghai Key Laboratory of Embryo and Reproduction EngineeringShanghai200040People's Republic of China

4. School of Computer and Information Technology & Beijing Key Lab of Traffic Data Analysis, Beijing Jiaotong UniversityBeijingPeople's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Cell Biology,Genetics,Molecular Biology,Modeling and Simulation,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-syb.2014.0066

Reference31 articles.

1. Atomistic modeling of protein–DNA interaction specificity: progress and applications

2. Inclusion of neighboring base interdependencies substantially improves genome-wide prokaryotic transcription factor binding site prediction

3. A non-independent energy-based multiple sequence alignment improves prediction of transcription factor binding sites

4. Use of structural DNA properties for the prediction of transcription-factor binding sites in Escherichia coli

5. Improved predictions of transcription factor binding sites using physicochemical features of DNA

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