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BMCBI
2008
138views more  BMCBI 2008»
13 years 7 months ago
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction
Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represent...
Ching-Wai Tan, David T. Jones
BMCBI
2006
143views more  BMCBI 2006»
13 years 7 months ago
Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction
Background: One of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because ...
Eric D. Scheeff, Philip E. Bourne
BMCBI
2010
97views more  BMCBI 2010»
13 years 7 months ago
SeqRate: sequence-based protein folding type classification and rates prediction
Background: Protein folding rate is an important property of a protein. Predicting protein folding rate is useful for understanding protein folding process and guiding protein des...
Guan Ning Lin, Zheng Wang, Dong Xu, Jianlin Cheng
BMCBI
2008
116views more  BMCBI 2008»
13 years 7 months ago
Impact of residue accessible surface area on the prediction of protein secondary structures
Background: The problem of accurate prediction of protein secondary structure continues to be one of the challenging problems in Bioinformatics. It has been previously suggested t...
Amir Momen-Roknabadi, Mehdi Sadeghi, Hamid Pezeshk...
BMCBI
2010
123views more  BMCBI 2010»
13 years 7 months ago
An improved classification of G-protein-coupled receptors using sequence-derived features
Background: G-protein-coupled receptors (GPCRs) play a key role in diverse physiological processes and are the targets of almost two-thirds of the marketed drugs. The 3 D structur...
Zhen-Ling Peng, Jian-Yi Yang, Xin Chen