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» Tests for gene clustering
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95
Voted
DEXAW
2009
IEEE
173views Database» more  DEXAW 2009»
15 years 7 months ago
Automatic Cluster Number Selection Using a Split and Merge K-Means Approach
Abstract—The k-means method is a simple and fast clustering technique that exhibits the problem of specifying the optimal number of clusters preliminarily. We address the problem...
Markus Muhr, Michael Granitzer
88
Voted
CSB
2005
IEEE
115views Bioinformatics» more  CSB 2005»
15 years 6 months ago
A New Clustering Strategy with Stochastic Merging and Removing Based on Kernel Functions
With hierarchical clustering methods, divisions or fusions, once made, are irrevocable. As a result, when two elements in a bottom-up algorithm are assigned to one cluster, they c...
Huimin Geng, Hesham H. Ali
77
Voted
ICANN
2005
Springer
15 years 6 months ago
High-Throughput Multi-dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data
Multidimensional Scaling (MDS) is a powerful dimension reduction technique for embedding high-dimensional data into a lowdimensional target space. Thereby, the distance relationshi...
Marc Strickert, Stefan Teichmann, Nese Sreenivasul...
86
Voted
GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
15 years 4 months ago
Using genetic programming to classify node positive patients in bladder cancer
Nodal staging has been identified as an independent indicator of prognosis. Quantitative RT-PCR data was taken for 70 genes associated with bladder cancer and genetic programming ...
Arpit A. Almal, Anirban P. Mitra, Ram H. Datar, Pe...
127
Voted
BMCBI
2011
14 years 7 months ago
RedundancyMiner: De-replication of redundant GO categories in microarray and proteomics analysis
Background: The Gene Ontology (GO) Consortium organizes genes into hierarchical categories based on biological process, molecular function and subcellular localization. Tools such...
Barry Zeeberg, Hongfang Liu, Ari B. Kahn, Martin E...