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RECOMB
2005
Springer
14 years 7 months ago
Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition
Abstract. Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e. segmenta...
Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanath...
NAR
2006
164views more  NAR 2006»
13 years 7 months ago
FISH - family identification of sequence homologues using structure anchored hidden Markov models
The FISH server is highly accurate in identifying the family membership of domains in a query protein sequence, even in the case of very low sequence identities to known homologue...
Jeanette Tångrot, Lixiao Wang, Bo Kågs...
BMCBI
2006
102views more  BMCBI 2006»
13 years 7 months ago
Protein secondary structure prediction for a single-sequence using hidden semi-Markov models
Background: The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algor...
Zafer Aydin, Yucel Altunbasak, Mark Borodovsky
BIBM
2008
IEEE
172views Bioinformatics» more  BIBM 2008»
14 years 2 months ago
Boosting Methods for Protein Fold Recognition: An Empirical Comparison
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
Yazhene Krishnaraj, Chandan K. Reddy
NAR
2006
74views more  NAR 2006»
13 years 7 months ago
HHrep: de novo protein repeat detection and the origin of TIM barrels
HHrep is a web server for the de novo identification of repeats in protein sequences, which is based on the pairwise comparison of profile hidden Markov models (HMMs). Its main st...
Johannes Söding, Michael Remmert, Andreas Bie...