DeepFam: deep learning based alignment-free method for protein family modeling and prediction
Author:
Affiliation:
1. Department of Computer Science and Engineering, Seoul National University, Seoul, Korea
2. Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Korea
3. Bioinformatics Institute, Seoul National University, Seoul, Korea
Funder
Collaborative Genome Program for Fostering New Post-Genome
National Research Foundation of Korea
NRF
Ministry of Science ICT and Future Planning
Next-Generation Information Computing Development Program
Ministry of Science
ICT
Institute for Information & communications Technology Promotion
IITP
MSIP
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/34/13/i254/25098060/bty275.pdf
Reference32 articles.
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3. UniProt: the universal protein knowledgebase;Apweiler;Nucleic Acids Res,2004
4. Continuous distributed representation of biological sequences for deep proteomics and genomics;Asgari;PloS One,2015
5. MEME SUITE: tools for motif discovery and searching;Bailey;Nucleic Acids Res,2009
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