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JMLR
2010
125views more  JMLR 2010»
13 years 3 months ago
On utility of gene set signatures in gene expression-based cancer class prediction
Machine learning methods that can use additional knowledge in their inference process are central to the development of integrative bioinformatics. Inclusion of background knowled...
Minca Mramor, Marko Toplak, Gregor Leban, Tomaz Cu...
BMCBI
2007
133views more  BMCBI 2007»
13 years 8 months ago
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
BMCBI
2007
148views more  BMCBI 2007»
13 years 8 months ago
p53FamTaG: a database resource of human p53, p63 and p73 direct target genes combining in silico prediction and microarray data
Background: The p53 gene family consists of the three genes p53, p63 and p73, which have polyhedral non-overlapping functions in pivotal cellular processes such as DNA synthesis a...
Elisabetta Sbisà, Domenico Catalano, Giorgi...
BMCBI
2007
176views more  BMCBI 2007»
13 years 8 months ago
Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue
Background: Micro- and macroarray technologies help acquire thousands of gene expression patterns covering important biological processes during plant ontogeny. Particularly, fait...
Marc Strickert, Nese Sreenivasulu, Björn Usad...
ECCB
2008
IEEE
14 years 3 months ago
SIRENE: supervised inference of regulatory networks
Living cells are the product of gene expression programs that involve the regulated transcription of thousands of genes. The elucidation of transcriptional regulatory networks in ...
Fantine Mordelet, Jean-Philippe Vert