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BMCBI
2010
123views more  BMCBI 2010»
13 years 18 days ago
Predicting conserved protein motifs with Sub-HMMs
Background: Profile HMMs (hidden Markov models) provide effective methods for modeling the conserved regions of protein families. A limitation of the resulting domain models is th...
Kevin Horan, Christian R. Shelton, Thomas Girke
BMCBI
2010
119views more  BMCBI 2010»
13 years 5 months ago
Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study
Background: Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key...
Qi Liu, Qian Xu, Vincent Wenchen Zheng, Hong Xue, ...
BMCBI
2011
13 years 18 days ago
DoBo: Protein domain boundary prediction by integrating evolutionary signals and machine learning
Background: Accurate identification of protein domain boundaries is useful for protein structure determination and prediction. However, predicting protein domain boundaries from a...
Jesse Eickholt, Xin Deng, Jianlin Cheng
BMCBI
2006
107views more  BMCBI 2006»
13 years 5 months ago
A reinforced merging methodology for mapping unique peptide motifs in members of protein families
Background: Members of a protein family often have highly conserved sequences; most of these sequences carry identical biological functions and possess similar three-dimensional (...
Hao-Teng Chang, Tun-Wen Pai, Tan-Chi Fan, Bo-Han S...
BMCBI
2006
111views more  BMCBI 2006»
13 years 5 months ago
PepDist: A New Framework for Protein-Peptide Binding Prediction based on Learning Peptide Distance Functions
Background: Many different aspects of cellular signalling, trafficking and targeting mechanisms are mediated by interactions between proteins and peptides. Representative examples...
Tomer Hertz, Chen Yanover