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JMLR
2010
125views more  JMLR 2010»
12 years 11 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...
BIOINFORMATICS
2005
134views more  BIOINFORMATICS 2005»
13 years 4 months ago
Outcome signature genes in breast cancer: is there a unique set?
Motivation: direct bearing whose expres Sorlie et al., 2 gene sets is a diseases (Lossos et al., 2004; Miklos and Maleszka, 2004), and the variables that could account questions i...
Liat Ein-Dor, Itai Kela, Gad Getz, David Givol, Ey...
BMCBI
2008
167views more  BMCBI 2008»
13 years 4 months ago
Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classificat
Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of ide...
Michael Gormley, Aydin Tozeren
BMCBI
2010
123views more  BMCBI 2010»
12 years 11 months ago
Predicting conserved protein motifs with Sub-HMMs
Background: Profile HMMs (hidden Markov models) provide effective methods for modeling the conserved regions of protein families. A limitation of the resulting domain models is th...
Kevin Horan, Christian R. Shelton, Thomas Girke
BMCBI
2007
173views more  BMCBI 2007»
13 years 4 months ago
Predicting state transitions in the transcriptome and metabolome using a linear dynamical system model
Background: Modelling of time series data should not be an approximation of input data profiles, but rather be able to detect and evaluate dynamical changes in the time series dat...
Ryoko Morioka, Shigehiko Kanaya, Masami Y. Hirai, ...