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» Gene Expression Clustering with Functional Mixture Models
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CSB
2005
IEEE
118views Bioinformatics» more  CSB 2005»
14 years 2 months ago
Gene Teams with Relaxed Proximity Constraint
Functionally related genes co-evolve, probably due to the strong selection pressure in evolution. Thus we expect that they are present in multiple genomes. Physical proximity amon...
Sun Kim, Jeong-Hyeon Choi, Jiong Yang
BMCBI
2010
124views more  BMCBI 2010»
13 years 9 months ago
A factor model to analyze heterogeneity in gene expression
Background: Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene d...
Yuna Blum, Guillaume Le Mignon, Sandrine Lagarrigu...
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
14 years 2 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
BMCBI
2007
186views more  BMCBI 2007»
13 years 9 months ago
GeneBins: a database for classifying gene expression data, with application to plant genome arrays
Background: To interpret microarray experiments, several ontological analysis tools have been developed. However, current tools are limited to specific organisms. Results: We deve...
Nicolas Goffard, Georg Weiller
BMCBI
2008
120views more  BMCBI 2008»
13 years 9 months ago
A protein interaction based model for schizophrenia study
Background: Schizophrenia is a complex disease with multiple factors contributing to its pathogenesis. In addition to environmental factors, genetic factors may also increase susc...
Pei-Chun Hsu, Ueng-Cheng Yang, Kuan-Hui Shih, Chih...