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» Evaluation of clustering algorithms for gene expression data
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SIAMCOMP
2008
123views more  SIAMCOMP 2008»
15 years 6 months ago
Approximation Algorithms for Biclustering Problems
One of the main goals in the analysis of microarray data is to identify groups of genes and groups of experimental conditions (including environments, individuals, and tissues) tha...
Lusheng Wang, Yu Lin, Xiaowen Liu
BMCBI
2007
143views more  BMCBI 2007»
15 years 6 months ago
Factor analysis for gene regulatory networks and transcription factor activity profiles
Background: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription fact...
Iosifina Pournara, Lorenz Wernisch
RECOMB
2004
Springer
16 years 7 months ago
Probabilistic discovery of overlapping cellular processes and their regulation
In this paper, we explore modeling overlapping biological processes. We discuss a probabilistic model of overlapping biological processes, gene membership in those processes, and ...
Alexis Battle, Eran Segal, Daphne Koller
ESORICS
2005
Springer
16 years 5 days ago
Privacy Preserving Clustering
The freedom and transparency of information flow on the Internet has heightened concerns of privacy. Given a set of data items, clustering algorithms group similar items together...
Somesh Jha, Louis Kruger, Patrick McDaniel
GCB
2008
Springer
103views Biometrics» more  GCB 2008»
15 years 7 months ago
Utilizing Promoter Pair Orientations for HMM-based Analysis of ChIP-chip Data
: Array-based analysis of chromatin immunoprecipitation data (ChIP-chip) is a powerful technique for identifying DNA target regions of individual transcription factors. Here, we pr...
Michael Seifert, Jens Keilwagen, Marc Strickert, I...