Improved disorder prediction by combination of orthogonal approaches.

TitleImproved disorder prediction by combination of orthogonal approaches.
Publication TypeJournal Article
Year of Publication2009
AuthorsSchlessinger, A, Punta, M, Yachdav, G, Kaján, L, Rost, B
JournalPLoS One
Volume4
Issue2
Paginatione4433
Date Published2009
ISSN1932-6203
KeywordsComputational Biology, Databases, Protein, Models, Molecular, Proteins, Reproducibility of Results
Abstract

Disordered proteins are highly abundant in regulatory processes such as transcription and cell-signaling. Different methods have been developed to predict protein disorder often focusing on different types of disordered regions. Here, we present MD, a novel META-Disorder prediction method that molds various sources of information predominantly obtained from orthogonal prediction methods, to significantly improve in performance over its constituents. In sustained cross-validation, MD not only outperforms its origins, but it also compares favorably to other state-of-the-art prediction methods in a variety of tests that we applied. Availability: http://www.rostlab.org/services/md/

DOI10.1371/journal.pone.0004433
Alternate JournalPLoS ONE
PubMed ID19209228
PubMed Central IDPMC2635965
Grant ListR01-LM07329 / LM / NLM NIH HHS / United States