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» Gene function prediction using labeled and unlabeled data
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BMCBI
2006
216views more  BMCBI 2006»
14 years 10 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...
BMCBI
2007
182views more  BMCBI 2007»
14 years 10 months ago
Identifying regulatory targets of cell cycle transcription factors using gene expression and ChIP-chip data
Background: ChIP-chip data, which indicate binding of transcription factors (TFs) to DNA regions in vivo, are widely used to reconstruct transcriptional regulatory networks. Howev...
Wei-Sheng Wu, Wen-Hsiung Li, Bor-Sen Chen
111
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RECOMB
2003
Springer
15 years 10 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
COLT
2008
Springer
14 years 12 months ago
An Information Theoretic Framework for Multi-view Learning
In the multi-view learning paradigm, the input variable is partitioned into two different views X1 and X2 and there is a target variable Y of interest. The underlying assumption i...
Karthik Sridharan, Sham M. Kakade
79
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BMCBI
2005
121views more  BMCBI 2005»
14 years 10 months ago
Automated methods of predicting the function of biological sequences using GO and BLAST
Background: With the exponential increase in genomic sequence data there is a need to develop automated approaches to deducing the biological functions of novel sequences with hig...
Craig E. Jones, Ute Baumann, Alfred L. Brown