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Qihao Qi

dblp:27/7063 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2009
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

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
0.112009
Non-negative matrix factorization of gene expression profiles: a plug-in for BRB-ArrayTools · Bioinform. 2009
Bioinformatics and computational biology › gene expression analysis › gene expression clustering
microarray data clustering
0.112009
Non-negative matrix factorization of gene expression profiles: a plug-in for BRB-ArrayTools · Bioinform. 2009
Bioinformatics and computational biology › gene expression analysis
differential expression analysis
0.012009
Non-negative matrix factorization of gene expression profiles: a plug-in for BRB-ArrayTools · Bioinform. 2009

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

semi-non-negative matrix factorization · 0.1non-negative matrix factorization · 0.1k-means clustering · 0.1
YearPublicationVenuePosition
2009 Non-negative matrix factorization of gene expression profiles: a plug-in for BRB-ArrayTools
abstract
SUMMARY: Non-negative matrix factorization (NMF) is an increasingly used algorithm for the analysis of complex high-dimensional data. BRB-ArrayTools is a widely used software system for the analysis of gene expression data with almost 9000 registered users in over 65 countries. We have developed a NMF analysis plug-in in BRB-ArrayTools for unsupervised sample clustering of microarray gene expression data. Our analysis tool also incorporates an algorithm for Semi-NMF which can handle both positive and negative elements for log-ratio data. Output includes a heat map of sample clusters and differentially expressed genes with extensive biological annotation. For comparison, output also includes the results of K-means clustering. AVAILABILITY: The NMF analysis plug-in is freely available in BRB-ArrayTools for non-commercial users. BRB-ArrayTools can be downloaded at http://linus.nci.nih.gov/BRB-ArrayTools.html. The algorithms used for NMF and Semi-NMF are available at ftp://linus.nci.nih.gov/pub/NMF.
Qihao Qi, Yingdong Zhao, Ming-Chung Li, Richard M. Simon
Bioinform.1