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» Predicting Time Series with Support Vector Machines
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159
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BMCBI
2008
228views more  BMCBI 2008»
15 years 3 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
126
Voted
BMCBI
2007
113views more  BMCBI 2007»
15 years 3 months ago
Analysis and prediction of antibacterial peptides
Background: Antibacterial peptides are important components of the innate immune system, used by the host to protect itself from different types of pathogenic bacteria. Over the l...
Sneh Lata, B. K. Sharma, G. P. S. Raghava
140
Voted
BMCBI
2010
179views more  BMCBI 2010»
15 years 3 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
146
Voted
BMCBI
2005
132views more  BMCBI 2005»
15 years 3 months ago
Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein
Background: A large number of papers have been published on analysis of microarray data with particular emphasis on normalization of data, detection of differentially expressed ge...
Gajendra P. S. Raghava, Joon H. Han
128
Voted
BMCBI
2010
120views more  BMCBI 2010»
15 years 3 months ago
KiDoQ: using docking based energy scores to develop ligand based model for predicting antibacterials
Background: Identification of novel drug targets and their inhibitors is a major challenge in the field of drug designing and development. Diaminopimelic acid (DAP) pathway is a u...
Aarti Garg, Rupinder Tewari, Gajendra P. S. Raghav...