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» Probabilistic topic modeling for genomic data interpretation
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KDD
2005
ACM
130views Data Mining» more  KDD 2005»
15 years 10 months ago
Simple and effective visual models for gene expression cancer diagnostics
In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
Gregor Leban, Minca Mramor, Ivan Bratko, Blaz Zupa...
BMCBI
2006
112views more  BMCBI 2006»
14 years 9 months ago
Algorithms for incorporating prior topological information in HMMs: application to transmembrane proteins
Background: Hidden Markov Models (HMMs) have been extensively used in computational molecular biology, for modelling protein and nucleic acid sequences. In many applications, such...
Pantelis G. Bagos, Theodore D. Liakopoulos, Stavro...
SIGIR
2009
ACM
15 years 4 months ago
On rank correlation and the distance between rankings
Rank correlation statistics are useful for determining whether a there is a correspondence between two measurements, particularly when the measures themselves are of less interest...
Ben Carterette
BMCBI
2011
14 years 4 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh
BMCBI
2008
88views more  BMCBI 2008»
14 years 9 months ago
Microarray-based gene set analysis: a comparison of current methods
Background: The analysis of gene sets has become a popular topic in recent times, with researchers attempting to improve the interpretability and reproducibility of their microarr...
Sarah Song, Michael A. Black