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CBMS
2005
IEEE
14 years 2 months ago
An Ontology-Driven Clustering Method for Supporting Gene Expression Analysis
The Gene Ontology (GO) is an important knowledge resource for biologists and bioinformaticians. This paper explores the integration of similarity information derived from GO into ...
Haiying Wang, Francisco Azuaje, Olivier Bodenreide...
BMCBI
2006
86views more  BMCBI 2006»
13 years 8 months ago
The impact of sample imbalance on identifying differentially expressed genes
Background: Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the p...
Kun Yang, Jianzhong Li, Hong Gao
BMCBI
2010
133views more  BMCBI 2010»
13 years 8 months ago
New components of the Dictyostelium PKA pathway revealed by Bayesian analysis of expression data
Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
Anup Parikh, Eryong Huang, Christopher Dinh, Blaz ...
BMCBI
2010
147views more  BMCBI 2010»
13 years 8 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
RECOMB
2003
Springer
14 years 9 months ago
An integrated probabilistic model for functional prediction of proteins
We develop an integrated probabilistic model to combine protein physical interactions, genetic interactions, highly correlated gene expression network, protein complex data, and d...
Minghua Deng, Ting Chen, Fengzhu Sun