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ISMB
2000
13 years 9 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
BMCBI
2010
136views more  BMCBI 2010»
13 years 7 months ago
A hub-attachment based method to detect functional modules from confidence-scored protein interactions and expression profiles
Background: Many research results show that the biological systems are composed of functional modules. Members in the same module usually have common functions. This is useful inf...
Chia-Hao Chin, Shu-Hwa Chen, Chin-Wen Ho, Ming-Tat...
BMCBI
2008
105views more  BMCBI 2008»
13 years 7 months ago
A gene pattern mining algorithm using interchangeable gene sets for prokaryotes
Background: Mining gene patterns that are common to multiple genomes is an important biological problem, which can lead us to novel biological insights. When family classification...
Meng Hu, Kwangmin Choi, Wei Su, Sun Kim, Jiong Yan...
BMCBI
2006
72views more  BMCBI 2006»
13 years 7 months ago
Selecting effective siRNA sequences by using radial basis function network and decision tree learning
Background: Although short interfering RNA (siRNA) has been widely used for studying gene functions in mammalian cells, its gene silencing efficacy varies markedly and there are o...
Shigeru Takasaki, Yoshihiro Kawamura, Akihiko Kona...
ISBRA
2009
Springer
14 years 2 months ago
Using Gene Expression Modeling to Determine Biological Relevance of Putative Regulatory Networks
Identifying gene regulatory networks from high-throughput gene expression data is one of the most important goals of bioinformatics, but it remains difficult to define what makes a...
Peter Larsen, Yang Dai