Integration of the Gene Ontology into an object-oriented architecture

BackgroundTo standardize gene product descriptions, a formal vocabulary defined as the Gene Ontology (GO) has been developed. GO terms have been categorized into biological processes, molecular functions, and cellular components. However, there is no single representation that integrates all the terms into one cohesive model. Furthermore, GO definitions have little information explaining the underlying architecture that forms these terms, such as the dynamic and static events occurring in a process. In contrast, object-oriented models have been developed to show dynamic and static events. A portion of the TGF-beta signaling pathway, which is involved in numerous cellular events including cancer, differentiation and development, was used to demonstrate the feasibility of integrating the Gene Ontology into an object-oriented model.ResultsUsing object-oriented models we have captured the static and dynamic events that occur during a representative GO process, "transforming growth factor-beta (TGF-beta) receptor complex assembly" (GO:0007181).ConclusionWe demonstrate that the utility of GO terms can be enhanced by object-oriented technology, and that the GO terms can be integrated into an object-oriented model by serving as a basis for the generation of object functions and attributes.

[1]  K. Kinzler,et al.  Human Smad3 and Smad4 are sequence-specific transcription activators. , 1998, Molecular cell.

[2]  Kuo-Chen Chou,et al.  A new hybrid approach to predict subcellular localization of proteins by incorporating gene ontology. , 2003, Biochemical and biophysical research communications.

[3]  Raymond B. Runyan,et al.  Requirement of type III TGF-beta receptor for endocardial cell transformation in the heart. , 1999, Science.

[4]  Michael Ashburner,et al.  Ontologies for biologists: a community model for the annotation of genomic data. , 2003 .

[5]  E. Davidson,et al.  Modeling transcriptional regulatory networks. , 2002, BioEssays : news and reviews in molecular, cellular and developmental biology.

[6]  Alan O'Callaghan,et al.  Object-Oriented Methods: Principles and Practice , 2000 .

[7]  Roland Eils,et al.  Applying Support Vector Machines for Gene ontology based gene function prediction , 2004, BMC Bioinformatics.

[8]  Denis Vivien,et al.  Direct binding of Smad3 and Smad4 to critical TGFβ‐inducible elements in the promoter of human plasminogen activator inhibitor‐type 1 gene , 1998, The EMBO journal.

[9]  K. Miyazono,et al.  Formation of hetero-oligomeric complexes of type I and type II receptors for transforming growth factor-beta. , 1994, The Journal of biological chemistry.

[10]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..

[11]  Søren Brunak,et al.  Prediction of human protein function according to Gene Ontology categories , 2003, Bioinform..

[12]  A Finney,et al.  Systems biology markup language: Level 2 and beyond. , 2003, Biochemical Society transactions.

[13]  Barry Smith,et al.  Controlled vocabularies in bioinformatics: a case study in the gene ontology , 2004 .

[14]  Jason E. Stewart,et al.  Design and implementation of microarray gene expression markup language (MAGE-ML) , 2002, Genome Biology.

[15]  John N. Weinstein,et al.  Development of Gene Ontology Tool for Biological Interpretation of Genomic and Proteomic Data , 2003, AMIA.

[16]  J. Schug,et al.  Predicting gene ontology functions from ProDom and CDD protein domains. , 2002, Genome research.

[17]  S. Somiari,et al.  Functional Relationship and Gene Ontology Classification of Breast Cancer Biomarkers , 2003 .

[18]  K. Bretonnel Cohen,et al.  The Compositional Structure of Gene Ontology Terms , 2003, Pacific Symposium on Biocomputing.

[19]  Xiao-Fan Wang,et al.  Tumor suppressor Smad4 is a transforming growth factor beta-inducible DNA binding protein , 1997, Molecular and cellular biology.

[20]  Emily Dimmer,et al.  The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology , 2004, Nucleic Acids Res..

[21]  Olivier Bodenreider,et al.  Comparing Associative Relationships among Equivalent Concepts across Ontologies , 2004, MedInfo.

[22]  S. Namkoong,et al.  Targeted cellular process profiling approach for uterine leiomyoma using cDNA microarray, proteomics and gene ontology analysis , 2003, International journal of experimental pathology.

[23]  Jonas S. Almeida,et al.  Local correlation of expression profiles with gene annotations-proof of concept for a general conciliatory method , 2005, Bioinform..

[24]  Leslie Lamport,et al.  Basic Concepts , 1981, Advanced Course: Distributed Systems.

[25]  Boris Adryan,et al.  Gene-Ontology-based clustering of gene expression data , 2004, Bioinform..

[26]  ChengXiang Zhai,et al.  Automatic annotation of protein motif function with Gene Ontology terms , 2003, BMC Bioinformatics.

[27]  J. Massagué,et al.  Smad2 nucleocytoplasmic shuttling by nucleoporins CAN/Nup214 and Nup153 feeds TGFbeta signaling complexes in the cytoplasm and nucleus. , 2002, Molecular cell.

[28]  J. Massagué,et al.  Ubiquitin-dependent degradation of TGF-β-activated Smad2 , 1999, Nature Cell Biology.

[29]  Bernhard O Palsson,et al.  Hierarchical thinking in network biology: the unbiased modularization of biochemical networks. , 2004, Trends in biochemical sciences.

[30]  W. Jim Zheng,et al.  Capturing biological information with class?Cresponsibility?Ccollaboration cards , 2005, Bioinform..

[31]  Liliana Attisano,et al.  SARA, a FYVE Domain Protein that Recruits Smad2 to the TGFβ Receptor , 1998, Cell.

[32]  Ian Graham Object-oriented methods (3rd ed.): principles & practice , 2001 .

[33]  J. Massagué,et al.  Ubiquitin-dependent degradation of , 1999 .

[34]  W. Jim Zheng,et al.  Object-oriented biological system integration: a SARS coronavirus example , 2005, Bioinform..

[35]  A. Arkin,et al.  Motifs, modules and games in bacteria. , 2003, Current opinion in microbiology.

[36]  J. Massagué TGF-beta signal transduction. , 1998, Annual review of biochemistry.

[37]  Steffen Schulze-Kremer,et al.  The Ontology of the Gene Ontology , 2003, AMIA.

[38]  Gene Ontology Consortium The Gene Ontology (GO) database and informatics resource , 2003 .

[39]  Duane Szafron,et al.  PA-GOSUB: a searchable database of model organism protein sequences with their predicted Gene Ontology molecular function and subcellular localization , 2004, Nucleic Acids Res..

[40]  Jan Komorowski,et al.  Predicting gene ontology biological process from temporal gene expression patterns. , 2003, Genome research.

[41]  C. Hill,et al.  Stoichiometry of Active Smad-Transcription Factor Complexes on DNA* , 2002, The Journal of Biological Chemistry.

[42]  Kara Dolinski,et al.  Saccharomyces Genome Database (SGD) provides secondary gene annotation using the Gene Ontology (GO) , 2002, Nucleic Acids Res..

[43]  Chris F. Taylor,et al.  A systematic approach to modeling, capturing, and disseminating proteomics experimental data , 2003, Nature Biotechnology.

[44]  C. Hill,et al.  Nucleocytoplasmic shuttling of Smads 2, 3, and 4 permits sensing of TGF-beta receptor activity. , 2002, Molecular cell.

[45]  J. Massagué,et al.  The nuclear import function of Smad2 is masked by SARA and unmasked by TGFb-dependent phosphorylation , 2000, Nature Cell Biology.

[46]  Liviu Badea,et al.  Functional Discrimination of Gene Expression Patterns in Terms of the Gene Ontology , 2002, Pacific Symposium on Biocomputing.

[47]  Ting Chen,et al.  Mapping gene ontology to proteins based on protein-protein interaction data , 2004, Bioinform..

[48]  R. Weinberg,et al.  Cooperative Binding of Transforming Growth Factor (TGF)-β2 to the Types I and II TGF-β Receptors (*) , 1995, The Journal of Biological Chemistry.

[49]  John R. Gilbertson,et al.  Microarray Data Mining Using Gene Ontology , 2004, MedInfo.

[50]  F Pinciroli,et al.  Towards biological knowledge mining by statistical analysis of Gene Ontology annotations , 2004 .

[51]  Patrick Lambrix,et al.  Evaluation of ontology development tools for bioinformatics , 2003, Bioinform..