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ECAI
2010
Springer
13 years 5 months ago
Feature Selection by Approximating the Markov Blanket in a Kernel-Induced Space
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
Qiang Lou, Zoran Obradovic
BMCBI
2008
158views more  BMCBI 2008»
13 years 8 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,...
BMCBI
2006
160views more  BMCBI 2006»
13 years 7 months ago
Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources
Background: In order to improve gene prediction, extrinsic evidence on the gene structure can be collected from various sources of information such as genome-genome comparisons an...
Mario Stanke, Oliver Schöffmann, Burkhard Mor...
BMCBI
2006
94views more  BMCBI 2006»
13 years 7 months ago
Novel knowledge-based mean force potential at the profile level
Background: The development and testing of functions for the modeling of protein energetics is an important part of current research aimed at understanding protein structure and f...
Qiwen Dong, Xiaolong Wang, Lei Lin
ICCV
2007
IEEE
14 years 2 months ago
Laplacian PCA and Its Applications
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
Deli Zhao, Zhouchen Lin, Xiaoou Tang