MRFy: remote homology detection for beta-structural proteins using Markov random fields and stochastic search

We introduce MRFy, a tool for protein remote homology detection that captures beta-strand dependencies in the Markov random field. Over a set of 11 SCOP beta-structural superfamilies, MRFy shows a 14 percent improvement in mean Area Under the Curve for the motif recognition problem as compared to HMMER, 25 percent improvement as compared to RAPTOR, 14 percent improvement as compared to HHPred, and a 18 percent improvement as compared to CNFPred and RaptorX. MRFy was implemented in the Haskell functional programming language, and parallelizes well on multi-core systems. MRFy is available, as source code as well as an executable, from http://mrfy.cs.tufts.edu/.

• Publication year

  2013

• Venue

  TCBB

• Publication date

  2013-04-24

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.1109/TCBB.2014.2344682arXiv 1304.6476PMID 26357074
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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