MoMo: discovery of statistically significant post-translational modification motifs
Author:
Affiliation:
1. Department of Genome Sciences, University of Washington, Seattle, WA, USA
2. Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA
3. Department of Pharmacology, University of Nevada, Reno, NV, USA
Abstract
Funder
NIH
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/35/16/2774/29154614/bty1058.pdf
Reference26 articles.
1. Discovery of protein phosphorylation motifs through exploratory data analysis;Chen;PloS One,2011
2. Biological sequence motif discovery using motif-x;Chou;Curr. Protocols Bioinform,2011
3. Phospho.ELM: a database of phosphorylation sites—update 2011;Dinkel;Nucleic Acids Res,2010
4. Discovering motifs in ranked lists of DNA sequences;Eden;PLoS Comput. Biol,2007
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