KOBAS server: a web-based platform for automated annotation and pathway identification

There is an increasing need to automatically annotate a set of genes or proteins (from genome sequencing, DNA microarray analysis or protein 2D gel experiments) using controlled vocabularies and identify the pathways involved, especially the statistically enriched pathways. We have previously demonstrated the KEGG Orthology (KO) as an effective alternative controlled vocabulary and developed a standalone KO-Based Annotation System (KOBAS). Here we report a KOBAS server with a friendly web-based user interface and enhanced functionalities. The server can support input by nucleotide or amino acid sequences or by sequence identifiers in popular databases and can annotate the input with KO terms and KEGG pathways by BLAST sequence similarity or directly ID mapping to genes with known annotations. The server can then identify both frequent and statistically enriched pathways, offering the choices of four statistical tests and the option of multiple testing correction. The server also has a ‘User Space’ in which frequent users may store and manage their data and results online. We demonstrate the usability of the server by finding statistically enriched pathways in a set of upregulated genes in Alzheimer's Disease (AD) hippocampal cornu ammonis 1 (CA1). KOBAS server can be accessed at .

[1]  Trey Ideker,et al.  VAMPIRE microarray suite: a web-based platform for the interpretation of gene expression data , 2005, Nucleic Acids Res..

[2]  Purvesh Khatri,et al.  Onto-Tools, the toolkit of the modern biologist: Onto-Express, Onto-Compare, Onto-Design and Onto-Translate , 2003, Nucleic Acids Res..

[3]  Li-Ping Wei,et al.  Transcriptome Profiling, Molecular Biological, and Physiological Studies Reveal a Major Role for Ethylene in Cotton Fiber Cell Elongation[W][OA] , 2006, The Plant Cell Online.

[4]  M. Ball,et al.  Gene expression profiling of 12633 genes in Alzheimer hippocampal CA1: Transcription and neurotrophic factor down‐regulation and up‐regulation of apoptotic and pro‐inflammatory signaling , 2002, Journal of neuroscience research.

[5]  C. Cotman,et al.  The Role of Caspase Cleavage of Tau in Alzheimer Disease Neuropathology , 2005, Journal of neuropathology and experimental neurology.

[6]  A. Aderem,et al.  Toll-like receptors in the induction of the innate immune response , 2000, Nature.

[7]  Hubert Hackl,et al.  PathwayExplorer: web service for visualizing high-throughput expression data on biological pathways , 2005, Nucleic Acids Res..

[8]  E. Masliah,et al.  Mechanisms of cell signaling and inflammation in Alzheimer's disease. , 2005, Current drug targets. Inflammation and allergy.

[9]  Geoffrey J. Barton,et al.  GOtcha: a new method for prediction of protein function assessed by the annotation of seven genomes , 2004, BMC Bioinformatics.

[10]  Kiyoko F. Aoki-Kinoshita,et al.  From genomics to chemical genomics: new developments in KEGG , 2005, Nucleic Acids Res..

[11]  Patrick L. McGeer,et al.  Inflammation, autotoxicity and Alzheimer disease , 2001, Neurobiology of Aging.

[12]  M. Kanehisa A database for post-genome analysis. , 1997, Trends in genetics : TIG.

[13]  Jihoon Kim,et al.  ArrayXPath: mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics , 2004, Nucleic Acids Res..

[14]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[15]  T. Speed,et al.  GOstat: find statistically overrepresented Gene Ontologies within a group of genes. , 2004, Bioinformatics.

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

[17]  Carl J. Schmidt,et al.  GoFigure: Automated Gene OntologyTM annotation , 2003, Bioinform..

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

[19]  Guoying Liu,et al.  NetAffx Gene Ontology Mining Tool: a visual approach for microarray data analysis. , 2004, Bioinformatics.

[20]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

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

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

[23]  Tao Cai,et al.  Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary , 2005, Bioinform..