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» A Markovian Approach for the Analysis of the gene Structure
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RECOMB
2002
Springer
14 years 7 months ago
Discovering local structure in gene expression data: the order-preserving submatrix problem
This paper concerns the discovery of patterns in gene expression matrices, in which each element gives the expression level of a given gene in a given experiment. Most existing me...
Amir Ben-Dor, Benny Chor, Richard M. Karp, Zohar Y...
ICPR
2008
IEEE
14 years 1 months ago
Gene function prediction using protein domain probability and hierarchical Gene Ontology information
The Gene Ontology (GO) is a controlled vocabulary of terms to describe protein functions. It also includes a hierarchical description of the relationships among the terms in the f...
Jaehee Jung, Michael R. Thon
CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
13 years 11 months ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang
ACAL
2007
Springer
14 years 1 months ago
An Integrated QAP-Based Approach to Visualize Patterns of Gene Expression Similarity
Abstract. This paper illustrates how the Quadratic Assignment Problem (QAP) is used as a mathematical model that helps to produce a visualization of microarray data, based on the r...
Mario Inostroza-Ponta, Alexandre Mendes, Regina Be...
BMCBI
2005
89views more  BMCBI 2005»
13 years 7 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg