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» Predicting relative performance of classifiers from samples
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BIBM
2007
IEEE
135views Bioinformatics» more  BIBM 2007»
14 years 2 months ago
Graph Kernel-Based Learning for Gene Function Prediction from Gene Interaction Network
Prediction of gene functions is a major challenge to biologists in the post-genomic era. Interactions between genes and their products compose networks and can be used to infer ge...
Xin Li, Zhu Zhang, Hsinchun Chen, Jiexun Li
KES
2008
Springer
13 years 6 months ago
Classification of Sporadic and BRCA1 Ovarian Cancer Based on a Genome-Wide Study of Copy Number Variations
Abstract. Motivation: Although studies have shown that genetic alterations are causally involved in numerous human diseases, still not much is known about the molecular mechanisms ...
Anneleen Daemen, Olivier Gevaert, Karin Leunen, Va...
PRL
2006
98views more  PRL 2006»
13 years 7 months ago
Data complexity assessment in undersampled classification of high-dimensional biomedical data
Regularized linear classifiers have been successfully applied in undersampled, i.e. small sample size/high dimensionality biomedical classification problems. Additionally, a desig...
Richard Baumgartner, Ray L. Somorjai
CSL
2010
Springer
13 years 7 months ago
Improving supervised learning for meeting summarization using sampling and regression
Meeting summarization provides a concise and informative summary for the lengthy meetings and is an effective tool for efficient information access. In this paper, we focus on ext...
Shasha Xie, Yang Liu
BMCBI
2008
154views more  BMCBI 2008»
13 years 7 months ago
Sequence based residue depth prediction using evolutionary information and predicted secondary structure
Background: Residue depth allows determining how deeply a given residue is buried, in contrast to the solvent accessibility that differentiates between buried and solvent-exposed ...
Hua Zhang, Tuo Zhang, Ke Chen 0003, Shiyi Shen, Ji...