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DILS
2008
Springer
13 years 9 months ago
Semi Supervised Spectral Clustering for Regulatory Module Discovery
We propose a novel semi-supervised clustering method for the task of gene regulatory module discovery. The technique uses data on dna binding as prior knowledge to guide the proces...
Alok Mishra, Duncan Gillies
PSB
2004
13 years 8 months ago
Motif Discovery in Heterogeneous Sequence Data
This paper introduces the first integrated algorithm designed to discover novel motifs in heterogeneous sequence data, which is comprised of coregulated genes from a single genome...
Amol Prakash, Mathieu Blanchette, Saurabh Sinha, M...
RECOMB
2002
Springer
14 years 7 months ago
From promoter sequence to expression: a probabilistic framework
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Our joint probabilistic model unifie...
Eran Segal, Yoseph Barash, Itamar Simon, Nir Fried...
BMCBI
2006
127views more  BMCBI 2006»
13 years 7 months ago
Using local gene expression similarities to discover regulatory binding site modules
Background: We present an approach designed to identify gene regulation patterns using sequence and expression data collected for Saccharomyces cerevisae. Our main goal is to rela...
Bartek Wilczynski, Torgeir R. Hvidsten, Andriy Kry...
PARMA
2004
136views Database» more  PARMA 2004»
13 years 8 months ago
Using Classification and Visualization on Pattern Databases for Gene Expression Data Analysis
Abstract. We are designing new data mining techniques on gene expression data, more precisely inductive querying techniques that extract a priori interesting bi-sets, i.e., sets of...
Céline Robardet, Ruggero G. Pensa, Jé...