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» A Heuristic Approach to Scoring Gene Clustering Algorithms
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CPM
2004
Springer
108views Combinatorics» more  CPM 2004»
14 years 1 months ago
Quadratic Time Algorithms for Finding Common Intervals in Two and More Sequences
A popular approach in comparative genomics is to locate groups or clusters of orthologous genes in multiple genomes and to postulate functional association between the genes contai...
Thomas Schmidt, Jens Stoye
BMCBI
2008
142views more  BMCBI 2008»
13 years 8 months ago
Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...
CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
14 years 7 days 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
BMCBI
2010
101views more  BMCBI 2010»
13 years 8 months ago
Hidden Markov model speed heuristic and iterative HMM search procedure
Background: Profile hidden Markov models (profile-HMMs) are sensitive tools for remote protein homology detection, but the main scoring algorithms, Viterbi or Forward, require con...
L. Steven Johnson, Sean R. Eddy, Elon Portugaly
BMCBI
2007
126views more  BMCBI 2007»
13 years 8 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...