Literature DB >> 18314575

Association analysis for large-scale gene set data.

Stefan A Kirov1, Bing Zhang, Jay R Snoddy.   

Abstract

High-throughput experiments in biology often produce sets of genes of potential interests. Some of those gene sets might be of considerable size. Therefore, computer-assisted analysis is necessary for the biological interpretation of the gene sets, and for creating working hypotheses, which can be tested experimentally. One obvious way to analyze gene set data is to associate the genes with a particular biological feature, for example, a given pathway. Statistical analysis could be used to evaluate if a gene set is truly associated with a feature. Over the past few years many tools that perform such analysis have been created. In this chapter, using WebGestalt as an example, it will be explained in detail how to associate gene sets with functional annotations, pathways, publication records, and protein domains.

Mesh:

Year:  2007        PMID: 18314575     DOI: 10.1007/978-1-59745-547-3_2

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  8 in total

1.  Proteomic analysis of oropharyngeal carcinomas reveals novel HPV-associated biological pathways.

Authors:  Robbert J C Slebos; Nico Jehmlich; Brandee Brown; Zhirong Yin; Christine H Chung; Wendell G Yarbrough; Daniel C Liebler
Journal:  Int J Cancer       Date:  2012-07-20       Impact factor: 7.396

2.  Gene-expression analysis of early- and late-maturation-stage rat enamel organ.

Authors:  Rodrigo S Lacruz; Charles E Smith; Yi-Bu Chen; Michael J Hubbard; Joseph G Hacia; Michael L Paine
Journal:  Eur J Oral Sci       Date:  2011-12       Impact factor: 2.612

3.  Identification of novel candidate genes involved in mineralization of dental enamel by genome-wide transcript profiling.

Authors:  Rodrigo S Lacruz; Charles E Smith; Pablo Bringas; Yi-Bu Chen; Susan M Smith; Malcolm L Snead; Ira Kurtz; Joseph G Hacia; Michael J Hubbard; Michael L Paine
Journal:  J Cell Physiol       Date:  2012-05       Impact factor: 6.384

4.  Identification of candidate downstream targets of TGFβ signaling during palate development by genome-wide transcript profiling.

Authors:  Richard C Pelikan; Junichi Iwata; Akiko Suzuki; Yang Chai; Joseph G Hacia
Journal:  J Cell Biochem       Date:  2013-04       Impact factor: 4.429

5.  Characterization of the MDSC proteome associated with metastatic murine mammary tumors using label-free mass spectrometry and shotgun proteomics.

Authors:  Angela M Boutté; W Hayes McDonald; Yu Shyr; Li Yang; P Charles Lin
Journal:  PLoS One       Date:  2011-08-10       Impact factor: 3.240

6.  Proteomic consequences of a single gene mutation in a colorectal cancer model.

Authors:  Patrick J Halvey; Bing Zhang; Robert J Coffey; Daniel C Liebler; Robbert J C Slebos
Journal:  J Proteome Res       Date:  2011-12-13       Impact factor: 4.466

7.  mtDNA depletion confers specific gene expression profiles in human cells grown in culture and in xenograft.

Authors:  Darren Magda; Philip Lecane; Julia Prescott; Patricia Thiemann; Xuan Ma; Patricia K Dranchak; Donna M Toleno; Krishna Ramaswamy; Kimberly D Siegmund; Joseph G Hacia
Journal:  BMC Genomics       Date:  2008-11-03       Impact factor: 3.969

8.  The gene expression profiles of induced pluripotent stem cells from individuals with childhood cerebral adrenoleukodystrophy are consistent with proposed mechanisms of pathogenesis.

Authors:  Xiao-Ming Wang; Wing Yan Yik; Peilin Zhang; Wange Lu; Patricia K Dranchak; Darryl Shibata; Steven J Steinberg; Joseph G Hacia
Journal:  Stem Cell Res Ther       Date:  2012-10-04       Impact factor: 6.832

  8 in total

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