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BIOINFORMATICS
2006
89views more  BIOINFORMATICS 2006»
14 years 11 months ago
Maximum significance clustering of oligonucleotide microarrays
Affymetrix high-density oligonucleotide microarrays measure expression of DNA transcripts using probesets, i.e. multiple probes per transcript. Usually, these multiple measurement...
Dick de Ridder, Frank J. T. Staal, Jacques J. M. v...
TSMC
2008
189views more  TSMC 2008»
14 years 11 months ago
Automatic Clustering Using an Improved Differential Evolution Algorithm
Differential evolution (DE) has emerged as one of the fast, robust, and efficient global search heuristics of current interest. This paper describes an application of DE to the aut...
Swagatam Das, Ajith Abraham, Amit Konar
85
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JCP
2008
133views more  JCP 2008»
14 years 11 months ago
DDSC : A Density Differentiated Spatial Clustering Technique
Finding clusters with widely differing sizes, shapes and densities in presence of noise and outliers is a challenging job. The DBSCAN is a versatile clustering algorithm that can f...
Bhogeswar Borah, Dhruba K. Bhattacharyya
BMCBI
2007
147views more  BMCBI 2007»
14 years 12 months ago
Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model
Background: Serial analysis of gene expression (SAGE) is used to obtain quantitative snapshots of the transcriptome. These profiles are count-based and are assumed to follow a Bin...
Scott D. Zuyderduyn
SYNASC
2005
IEEE
170views Algorithms» more  SYNASC 2005»
15 years 5 months ago
Density Based Clustering with Crowding Differential Evolution
The aim of this work is to analyze the applicability of crowding differential evolution to unsupervised clustering. The basic idea of this approach, interpreting the clustering pr...
Daniela Zaharie