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K. Ohm

dblp:42/5777 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
gene expression analysis
0.012004
GeneCluster 2.0: an advanced toolset for bioarray analysis · Bioinform. 2004
Bioinformatics and computational biology › gene expression analysis
sample classification
0.012004
GeneCluster 2.0: an advanced toolset for bioarray analysis · Bioinform. 2004
Bioinformatics and computational biology › gene expression analysis › gene expression classification
marker gene selection
0.012004
GeneCluster 2.0: an advanced toolset for bioarray analysis · Bioinform. 2004

Methods — techniques the papers use, named apart from their topics

weighted voting · 0.0self-organizing map · 0.0permutation test · 0.0k-nearest neighbor · 0.0
YearPublicationVenuePosition
2004 GeneCluster 2.0: an advanced toolset for bioarray analysis
abstract
SUMMARY: GeneCluster 2.0 is a software package for analyzing gene expression and other bioarray data, giving users a variety of methods to build and evaluate class predictors, visualize marker lists, cluster data and validate results. GeneCluster 2.0 greatly expands the data analysis capabilities of GeneCluster 1.0 by adding classification, class discovery and permutation test methods. It includes algorithms for building and testing supervised models using weighted voting and k-nearest neighbor algorithms, a module for systematically finding and evaluating clustering via self-organizing maps, and modules for marker gene selection and heat map visualization that allow users to view and sort samples and genes by many criteria. GeneCluster 2.0 is a stand-alone Java application and runs on any platform that supports the Java Runtime Environment version 1.3.1 or greater. AVAILABILITY: http://www.broad.mit.edu/cancer/software
Michael Reich, K. Ohm, Michael Angelo, Pablo Tamayo, Jill P. Mesirov
Bioinform.2