Application of Biostatistics and Bioinformatics Tools to Identify Putative Transcription Factor-Gene Regulatory Network of Ankylosing Spondylitis and Sarcoidosis

DOI10.1080/03610920902898472zbMath1177.62126OpenAlexW2012929111WikidataQ42949245 ScholiaQ42949245MaRDI QIDQ3652664

Stephen R. Planck, Dongseok Choi, Christina A. Harrington, S. M. Sharma, James T. Rosenbaum, Sirichai Pasadhika, Zhixin Kang, Justine R. Smith

Publication date: 16 December 2009

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2796828

zbMATH Keywords

cluster analysisgene expressiontranscription factorsarcoidosisankylosing spondylitisaffymetrix microarraystightclust

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40) Systems biology, networks (92C42)

Related Items (3)

Marginal integration for nonparametric causal inference ⋮ An adaptively weighted statistic for detecting differential gene expression when combining multiple transcriptomic studies ⋮ Network inference and biological dynamics

Uses Software

• dynamicTreeCut

Cites Work

• Algorithm AS 136: A K-Means Clustering Algorithm
• Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection
• Significance analysis of microarrays applied to the ionizing radiation response
• Finding Groups in Data
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• A Model-Based Background Adjustment for Oligonucleotide Expression Arrays
• Statistical significance for genomewide studies
• Exploration, normalization, and summaries of high density oligonucleotide array probe level data
• Tight Clustering: A Resampling‐Based Approach for Identifying Stable and Tight Patterns in Data

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