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» Evaluation of clustering algorithms for gene expression data
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GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
15 years 7 months ago
Particle swarm clustering ensemble
Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recent...
Abbas Ahmadi, Fakhri Karray, Mohamed Kamel
DILS
2008
Springer
15 years 8 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
BMCBI
2005
112views more  BMCBI 2005»
15 years 6 months ago
Vector analysis as a fast and easy method to compare gene expression responses between different experimental backgrounds
Background: Gene expression studies increasingly compare expression responses between different experimental backgrounds (genetic, physiological, or phylogenetic). By focusing on ...
Rainer Breitling, Patrick Armengaud, Anna Amtmann
BMCBI
2010
154views more  BMCBI 2010»
15 years 6 months ago
Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data
Background: A major goal of molecular biology is determining the mechanisms that control the transcription of genes. Motif Enrichment Analysis (MEA) seeks to determine which DNA-b...
Robert C. McLeay, Timothy L. Bailey
ANCS
2007
ACM
15 years 10 months ago
An improved algorithm to accelerate regular expression evaluation
Modern network intrusion detection systems need to perform regular expression matching at line rate in order to detect the occurrence of critical patterns in packet payloads. Whil...
Michela Becchi, Patrick Crowley