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» DIG - a system for gene annotation and functional discovery
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CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
13 years 11 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
2004
252views more  BMCBI 2004»
13 years 5 months ago
Applying Support Vector Machines for Gene ontology based gene function prediction
Background: The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to ann...
Arunachalam Vinayagam, Rainer König, Jutta Mo...
BMCBI
2006
137views more  BMCBI 2006»
13 years 5 months ago
GOPET: A tool for automated predictions of Gene Ontology terms
Background: Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These method...
Arunachalam Vinayagam, Coral del Val, Falk Schuber...
RECOMB
2003
Springer
14 years 5 months ago
Whole-genome comparative annotation and regulatory motif discovery in multiple yeast species
In [13] we reported the genome sequences of S. paradoxus, S. mikatae and S. bayanus and compared these three yeast species to their close relative, S. cerevisiae. Genome-wide comp...
Manolis Kamvysselis, Nick Patterson, Bruce Birren,...
BMCBI
2008
259views more  BMCBI 2008»
13 years 5 months ago
DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcripti
Background: A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted w...
Evert-Jan Blom, Sacha A. F. T. van Hijum, Klaas J....