High-Throughput GoMiner, an 'industrial-strength' integrative gene ontology tool for interpretation of multiple-microarray experiments, with application to studies of Common Variable Immune Deficiency (CVID)
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* Corresponding author: John N Weinstein weinstein@dtpax2.ncifcrf.gov
- † Equal contributors
BMC Bioinformatics 2005, 6:168 doi:10.1186/1471-2105-6-168
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BioMed Central: 26 citations
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Research
Robert W Li, Manuela Rinaldi, Anthony V Capuco Veterinary Research 2011, 42:114 (30 November 2011) |
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Proceedings
Building interpretable fuzzy models for high dimensional data analysis in cancer diagnosis Zhenyu Wang, Vasile Palade BMC Genomics 2011, 12(Suppl 2):S5 (27 July 2011) |
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Proceedings
Martin Ehler, Vinodh N Rajapakse, Barry R Zeeberg, Brian P Brooks, Jacob Brown, Wojciech Czaja, Robert F Bonner BMC Proceedings 2011, 5(Suppl 2):S3 (28 April 2011) |
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Research
A human functional protein interaction network and its application to cancer data analysis Guanming Wu, Xin Feng, Lincoln Stein Genome Biology 2010, 11:R53 (19 May 2010) A high-quality human functional protein interaction network is constructed. Its utility is demonstrated in the identification of cancer candidate genes. |
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Research article
Predicting environmental chemical factors associated with disease-related gene expression data Chirag J Patel, Atul J Butte BMC Medical Genomics 2010, 3:17 (6 May 2010) |
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Research article
Alissar Nehmé, Edward K Lobenhofer, W Daniel Stamer, Jeffrey L Edelman BMC Medical Genomics 2009, 2:58 (10 September 2009) |
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Research article
Interactome and Gene Ontology provide congruent yet subtly different views of a eukaryotic cell Antonio Marco, Ignacio Marín BMC Systems Biology 2009, 3:69 (15 July 2009) |
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Software
Ming Yi, Uma Mudunuri, Anney Che, Robert M Stephens BMC Bioinformatics 2009, 10:200 (29 June 2009) |
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Research
MicroRNA and gene expression patterns in the differentiation of human embryonic stem cells Jiaqiang Ren, Ping Jin, Ena Wang, Francesco M Marincola, David F Stroncek Journal of Translational Medicine 2009, 7:20 (23 March 2009) |
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Research article
An Open Access Database of Genome-wide Association Results Andrew D Johnson, Christopher J O'Donnell BMC Medical Genetics 2009, 10:6 (22 January 2009) A new centralized open access database containing the results of 118 genome-wide association (GWA) studies shows considerable heterogeneity in the data and provides a potential resource for result sharing between a wide community of researchers.
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Short Report
Advanced spot quality analysis in two-colour microarray experiments Mikalai Yatskou, Eugene Novikov, Guillaume Vetter, Arnaud Muller, Emmanuel Barillot, Laurent Vallar, Evelyne Friederich BMC Research Notes 2008, 1:80 (17 September 2008) This article is part of a collection on Microarray normalization... |
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Method
Edward K Lobenhofer, J Todd Auman, Pamela E Blackshear, Gary A Boorman, Pierre R Bushel, Michael L Cunningham, Jennifer M Fostel, Kevin Gerrish, Alexandra N Heinloth, Richard D Irwin, David E Malarkey, B Alex Merrick, Stella O Sieber, Charles J Tucker, Sandra M Ward, Ralph E Wilson, Patrick Hurban, Raymond W Tennant, Richard S Paules Genome Biology 2008, 9:R100 (20 June 2008) Histopathology, clinical chemistry, hematology and gene expression data were collected from the rat liver and blood after treatment with eight known hepatotoxins. |
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Research article
Lingkang Huang, Alexandra N Heinloth, Zhao-Bang Zeng, Richard S Paules, Pierre R Bushel BMC Genomics 2008, 9:288 (16 June 2008) |
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Methodology article
VennMaster: Area-proportional Euler diagrams for functional GO analysis of microarrays Hans A Kestler, André Müller, Johann M Kraus, Malte Buchholz, Thomas M Gress, Hongfang Liu, David W Kane, Barry R Zeeberg, John N Weinstein BMC Bioinformatics 2008, 9:67 (29 January 2008) |
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Methodology article
Antonio Marco, Ignacio Marín BMC Bioinformatics 2007, 8:442 (15 November 2007) |
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Method
Gabriel S Eichler, Mark Reimers, David Kane, John N Weinstein Genome Biology 2007, 8:R187 (10 September 2007) The LeFE algorithm has been developed to address the complex, non-linear regulation of gene expression. |
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Software
Da Huang, Brad T Sherman, Qina Tan, Jack R Collins, W Gregory Alvord, Jean Roayaei, Robert Stephens, Michael W Baseler, H Clifford Lane, Richard A Lempicki Genome Biology 2007, 8:R183 (4 September 2007) The DAVID gene functional classification tool uses a novel fuzzy clustering algorithm to condense a list of genes or associated biological terms into organized classes of related genes or biology, called biological modules. |
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Research article
Ying Hao, Sumita Sood, George Triadafilopoulos, Jong Kim, Zheng Wang, Peyman Sahbaie, M Bishr Omary, Anson W Lowe BMC Gastroenterology 2007, 7:24 (27 June 2007) |
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Database
Ari B Kahn, Michael C Ryan, Hongfang Liu, Barry R Zeeberg, D Curtis Jamison, John N Weinstein BMC Bioinformatics 2007, 8:75 (5 March 2007) |
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Software
FUNC: a package for detecting significant associations between gene sets and ontological annotations Kay Prüfer, Bjoern Muetzel, Hong-Hai Do, Gunter Weiss, Philipp Khaitovich, Erhard Rahm, Svante Pääbo, Michael Lachmann, Wolfgang Enard BMC Bioinformatics 2007, 8:41 (6 February 2007) |
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Software
Björn Usadel, Axel Nagel, Dirk Steinhauser, Yves Gibon, Oliver E Bläsing, Henning Redestig, Nese Sreenivasulu, Leonard Krall, Matthew A Hannah, Fabien Poree, Alisdair R Fernie, Mark Stitt BMC Bioinformatics 2006, 7:535 (18 December 2006) |
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Research article
Mining expressed sequence tags identifies cancer markers of clinical interest Fabien Campagne, Lucy Skrabanek BMC Bioinformatics 2006, 7:481 (1 November 2006) |
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Proceedings
Hongmei Sun, Hong Fang, Tao Chen, Roger Perkins, Weida Tong BMC Bioinformatics 2006, 7(Suppl 2):S23 (26 September 2006) |
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Methodology article
Cluster analysis of protein array results via similarity of Gene Ontology annotation Cheryl Wolting, C Jane McGlade, David Tritchler BMC Bioinformatics 2006, 7:338 (12 July 2006) |
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Software
STEM: a tool for the analysis of short time series gene expression data Jason Ernst, Ziv Bar-Joseph BMC Bioinformatics 2006, 7:191 (5 April 2006) |
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Research
The molecular portrait of in vitro growth by meta-analysis of gene-expression profiles Rickard Sandberg, Ingemar Ernberg Genome Biology 2005, 6:R65 (27 July 2005) A meta analysis comparing 60 tumor cell lines, 135 normal tissue samples and 176 tumor tissue samples in humans shows significant differential expression between cell lines and tissues of around 30% of the 7,000 genes analyzed. |