ProfCom: a web tool for profiling the complex functionality of gene groups identified from high-throughput data

ProfCom is a web-based tool for the functional interpretation of a gene list that was identified to be related by experiments. A trait which makes ProfCom a unique tool is an ability to profile enrichments of not only available Gene Ontology (GO) terms but also of ‘complex functions’. A ‘Complex function’ is constructed as Boolean combination of available GO terms. The complex functions inferred by ProfCom are more specific in comparison to single terms and describe more accurately the functional role of genes. ProfCom provides a user friendly dialog-driven web page submission available for several model organisms and supports most available gene identifiers. In addition, the web service interface allows the submission of any kind of annotation data. ProfCom is freely available at http://webclu.bio.wzw.tum.de/profcom/.

[1]  Joaquín Dopazo,et al.  BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments , 2006, Nucleic Acids Res..

[2]  May D. Wang,et al.  GoMiner: a resource for biological interpretation of genomic and proteomic data , 2003, Genome Biology.

[3]  P. Khatri,et al.  Profiling gene expression using onto-express. , 2002, Genomics.

[4]  Hedi Peterson,et al.  g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments , 2007, Nucleic Acids Res..

[5]  Purvesh Khatri,et al.  Babel's tower revisited: a universal resource for cross-referencing across annotation databases , 2006, Bioinform..

[6]  Martin Vingron,et al.  Improved detection of overrepresentation of Gene-Ontology annotations with parent-child analysis , 2007, Bioinform..

[7]  David S. Wishart,et al.  The CyberCell Database (CCDB): a comprehensive, self-updating, relational database to coordinate and facilitate in silico modeling of Escherichia coli , 2004, Nucleic Acids Res..

[8]  Joaquín Dopazo,et al.  The role of the environment in Parkinson's disease. , 1996, Nucleic Acids Res..

[9]  Thomas Lengauer,et al.  Improved scoring of functional groups from gene expression data by decorrelating GO graph structure , 2006, Bioinform..

[10]  Joaquín Dopazo,et al.  FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes , 2004, Bioinform..

[11]  David Martin,et al.  GOToolBox: functional analysis of gene datasets based on Gene Ontology , 2004, Genome Biology.

[12]  Purvesh Khatri,et al.  Ontological analysis of gene expression data: current tools, limitations, and open problems , 2005, Bioinform..

[13]  Tatiana Tatusova,et al.  NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins , 2004, Nucleic Acids Res..

[14]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[15]  Igor V. Tetko,et al.  A systematic approach to infer biological relevance and biases of gene network structures , 2006, Nucleic acids research.

[16]  Bing Zhang,et al.  WebGestalt: an integrated system for exploring gene sets in various biological contexts , 2005, Nucleic Acids Res..

[17]  Guoying Liu,et al.  NetAffx: Affymetrix probesets and annotations , 2003, Nucleic Acids Res..

[18]  C. Revankar,et al.  Altered Ca2+ homeostasis in polymorphonuclear leukocytes from chronic myeloid leukaemia patients , 2006, Molecular Cancer.

[19]  Gordon B Mills,et al.  Patterns of Gene Expression in Different Histotypes of Epithelial Ovarian Cancer Correlate with Those in Normal Fallopian Tube, Endometrium, and Colon , 2005, Clinical Cancer Research.

[20]  Georg F. Weiller,et al.  PathExpress: a web-based tool to identify relevant pathways in gene expression data , 2007, Nucleic Acids Res..

[21]  H. Mewes,et al.  Complex functionality of gene groups identified from high-throughput data. , 2006, Journal of molecular biology.

[22]  P. Khatri,et al.  A systems biology approach for pathway level analysis. , 2007, Genome research.

[23]  Dmitrij Frishman,et al.  MIPS: analysis and annotation of proteins from whole genomes in 2005 , 2005, Nucleic Acids Res..

[24]  Francesco Pinciroli,et al.  GFINDer: Genome Function INtegrated Discoverer through dynamic annotation, statistical analysis, and mining , 2004, Nucleic Acids Res..

[25]  Joaquín Dopazo,et al.  BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments , 2005, Nucleic Acids Res..

[26]  Purvesh Khatri,et al.  Onto-Tools: an ensemble of web-accessible, ontology-based tools for the functional design and interpretation of high-throughput gene expression experiments , 2004, Nucleic Acids Res..

[27]  H. Mewes,et al.  BIOREL: The benchmark resource to estimate the relevance of the gene networks , 2006, FEBS letters.

[28]  Purvesh Khatri,et al.  Onto-Tools: new additions and improvements in 2006 , 2007, Nucleic Acids Res..

[29]  Andreas Prlic,et al.  Ensembl 2006 , 2005, Nucleic Acids Res..

[30]  S. S. Young,et al.  Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment , 1993 .

[31]  Chris Sander,et al.  Characterizing gene sets with FuncAssociate , 2003, Bioinform..

[32]  Ioannis Xenarios,et al.  DIP: The Database of Interacting Proteins: 2001 update , 2001, Nucleic Acids Res..

[33]  J. Carazo,et al.  GENECODIS: a web-based tool for finding significant concurrent annotations in gene lists , 2007, Genome Biology.

[34]  Alex Bateman,et al.  The InterPro database, an integrated documentation resource for protein families, domains and functional sites , 2001, Nucleic Acids Res..