Sequence-based protein-protein interaction prediction via support vector machine
- 1 October 2010
- journal article
- research article
- Published by Springer Science and Business Media LLC in Journal of Systems Science and Complexity
- Vol. 23 (5), 1012-1023
- https://doi.org/10.1007/s11424-010-0214-z
Abstract
No abstract availableKeywords
This publication has 36 references indexed in Scilit:
- Disease-Aging Network Reveals Significant Roles of Aging Genes in Connecting Genetic DiseasesPLoS Computational Biology, 2009
- Using support vector machine combined with auto covariance to predict protein–protein interactions from protein sequencesNucleic Acids Research, 2008
- Predicting Protein−Protein Interactions from Sequences in a Hybridization SpaceJournal of Proteome Research, 2005
- Predicting protein–protein interactions using signature productsBioinformatics, 2004
- Revisiting the codon adaptation index from a whole-genome perspective: analyzing the relationship between gene expression and codon occurrence in yeast using a variety of modelsNucleic Acids Research, 2003
- Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometryNature, 2002
- Functional organization of the yeast proteome by systematic analysis of protein complexesNature, 2002
- Global Analysis of Protein Activities Using Proteome ChipsScience, 2001
- A comprehensive two-hybrid analysis to explore the yeast protein interactomeProceedings of the National Academy of Sciences of the United States of America, 2001
- A novel genetic system to detect protein–protein interactionsNature, 1989