Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple species-Reference-Cited by-同舟云学术

Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple species

Published:2018-09-19 Issue:8 Volume:35 Page:1326-1333
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Wei Leyi¹^ORCID,Luan Shasha¹,Nagai Luis Augusto Eijy²,Su Ran³,Zou Quan¹⁴

Affiliation:

1. School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, China

2. Lab of Functional Analysis In Silico, Institute of Medical Science, University of Tokyo, Tokyo, Japan

3. School of Computer Software, College of Intelligence and Computing, Tianjin University, Tianjin, China

4. Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/35/8/1326/28500770/bty824.pdf

Reference50 articles.

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3. Prediction of bacteriophage proteins located in the host cell using hybrid features;Cheng;Chemometr. Intell. Lab. Syst,2018

4. DNA modification by methyltransferases;Cheng;Curr. Opin. Struct. Biol,1995

5. Predicting protein–protein interactions via multivariate mutual information of protein sequences;Ding;BMC Bioinformatics,2016

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