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» Predicting Nucleolar Proteins Using Support-Vector Machines
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CORR
2007
Springer
113views Education» more  CORR 2007»
13 years 7 months ago
Virtual screening with support vector machines and structure kernels
Support vector machines and kernel methods have recently gained considerable attention in chemoinformatics. They offer generally good performance for problems of supervised classi...
Pierre Mahé, Jean-Philippe Vert
CEC
2007
IEEE
13 years 11 months ago
Prediction of protein interactions by combining genetic algorithm with SVM method
This paper proposes a novel hybrid GA/SVM method that can predict the interactions between proteins intermediated by the protein-domain relations. Firstly, we represented a protein...
Bing Wang, Lu-Sheng Ge, Wen-You Jia, Li Liu, Fu-Ch...
BMCBI
2010
98views more  BMCBI 2010»
13 years 7 months ago
Learning to predict expression efficacy of vectors in recombinant protein production
Background: Recombinant protein production is a useful biotechnology to produce a large quantity of highly soluble proteins. Currently, the most widely used production system is t...
Wen-Ching Chan, Po-Huang Liang, Yan-Ping Shih, Uen...
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
13 years 11 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa
BMCBI
2008
93views more  BMCBI 2008»
13 years 7 months ago
VirulentPred: a SVM based prediction method for virulent proteins in bacterial pathogens
Background: Prediction of bacterial virulent protein sequences has implications for identification and characterization of novel virulence-associated factors, finding novel drug/v...
Aarti Garg, Dinesh Gupta