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BMCBI
2004
208views more  BMCBI 2004»
13 years 7 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein
BMCBI
2007
119views more  BMCBI 2007»
13 years 7 months ago
Efficacy of different protein descriptors in predicting protein functional families
Background: Sequence-derived structural and physicochemical descriptors have frequently been used in machine learning prediction of protein functional families, thus there is a ne...
Serene A. K. Ong, Hong Huang Lin, Yu Zong Chen, Ze...
BMCBI
2007
133views more  BMCBI 2007»
13 years 7 months ago
AGGRESCAN: a server for the prediction and evaluation of "hot spots" of aggregation in polypeptides
Background: Protein aggregation correlates with the development of several debilitating human disorders of growing incidence, such as Alzheimer's and Parkinson's disease...
Oscar Conchillo-Solé, Natalia S. de Groot, ...
BMCBI
2006
125views more  BMCBI 2006»
13 years 7 months ago
Automated functional classification of experimental and predicted protein structures
Background: Proteins that are similar in sequence or structure may perform different functions in nature. In such cases, function cannot be inferred from sequence or structural si...
Kai Wang, Ram Samudrala
NAR
2008
101views more  NAR 2008»
13 years 7 months ago
PVS: a web server for protein sequence variability analysis tuned to facilitate conserved epitope discovery
We have developed PVS (Protein Variability Server), a web-based tool that uses several variability metrics to compute the absolute site variability in multiple protein-sequence al...
Maria Garcia-Boronat, Carmen M. Diez-Rivero, Ellis...