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BMCBI
2011
14 years 8 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
JIB
2006
106views more  JIB 2006»
15 years 4 months ago
A structural keystone for drug design
3D-structures of proteins and potential ligands are the cornerstones of rational drug design. The first brick to build upon is selecting a protein target and finding out whether b...
Kristian Rother, Mathias Dunkel, Elke Michalsky, S...
BMCBI
2004
208views more  BMCBI 2004»
15 years 4 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
GECCO
2003
Springer
123views Optimization» more  GECCO 2003»
15 years 10 months ago
Benefits of Implicit Redundant Genetic Algorithms for Structural Damage Detection in Noisy Environments
A robust structural damage detection method that can handle noisy frequency response function information is discussed. The inherent unstructured nature of damage detection problem...
Anne M. Raich, Tamás Liszkai
153
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BMCBI
2010
106views more  BMCBI 2010»
15 years 4 months ago
Multiple structure alignment and consensus identification for proteins
Background: An algorithm is presented to compute a multiple structure alignment for a set of proteins and to generate a consensus (pseudo) protein which captures common substructu...
Ivaylo Ilinkin, Jieping Ye, Ravi Janardan