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» Predicting Nucleolar Proteins Using Support-Vector Machines
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126
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TKDE
2008
123views more  TKDE 2008»
15 years 3 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko
122
Voted
BMCBI
2008
158views more  BMCBI 2008»
15 years 3 months ago
Real value prediction of protein solvent accessibility using enhanced PSSM features
Background: Prediction of protein solvent accessibility, also called accessible surface area (ASA) prediction, is an important step for tertiary structure prediction directly from...
Darby Tien-Hao Chang, Hsuan-Yu Huang, Yu-Tang Syu,...
109
Voted
BMCBI
2007
91views more  BMCBI 2007»
15 years 3 months ago
A machine learning approach for the identification of odorant binding proteins from sequence-derived properties
Background: Odorant binding proteins (OBPs) are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as od...
Ganesan Pugalenthi, E. Ke Tang, Ponnuthurai N. Sug...
131
Voted
BMCBI
2008
123views more  BMCBI 2008»
15 years 3 months ago
Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach
Background: Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing a...
Firoz Anwar, Syed Murtuza Baker, Taskeed Jabid, Md...
142
Voted
BMCBI
2008
102views more  BMCBI 2008»
15 years 3 months ago
Fast splice site detection using information content and feature reduction
Background: Accurate identification of splice sites in DNA sequences plays a key role in the prediction of gene structure in eukaryotes. Already many computational methods have be...
A. K. M. A. Baten, Saman K. Halgamuge, Bill C. H. ...