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1.
J Biomed Inform ; 44(1): 80-6, 2011 Feb.
Article in English | MEDLINE | ID: mdl-20152934

ABSTRACT

The Gene Ontology (GO) consists of nearly 30,000 classes for describing the activities and locations of gene products. Manual maintenance of ontology of this size is a considerable effort, and errors and inconsistencies inevitably arise. Reasoners can be used to assist with ontology development, automatically placing classes in a subsumption hierarchy based on their properties. However, the historic lack of computable definitions within the GO has prevented the user of these tools. In this paper, we present preliminary results of an ongoing effort to normalize the GO by explicitly stating the definitions of compositional classes in a form that can be used by reasoners. These definitions are partitioned into mutually exclusive cross-product sets, many of which reference other OBO Foundry candidate ontologies for chemical entities, proteins, biological qualities and anatomical entities. Using these logical definitions we are gradually beginning to automate many aspects of ontology development, detecting errors and filling in missing relationships. These definitions also enhance the GO by weaving it into the fabric of a wider collection of interoperating ontologies, increasing opportunities for data integration and enhancing genomic analyses.


Subject(s)
Database Management Systems , Databases, Genetic , Genetics , Vocabulary, Controlled , Anatomy , Animals , Cell Biology , Genes , Humans , Molecular Biology
2.
Microbiol Mol Biol Rev ; 74(4): 479-503, 2010 Dec.
Article in English | MEDLINE | ID: mdl-21119014

ABSTRACT

Microbes form intimate relationships with hosts (symbioses) that range from mutualism to parasitism. Common microbial mechanisms involved in a successful host association include adhesion, entry of the microbe or its effector proteins into the host cell, mitigation of host defenses, and nutrient acquisition. Genes associated with these microbial mechanisms are known for a broad range of symbioses, revealing both divergent and convergent strategies. Effective comparisons among these symbioses, however, are hampered by inconsistent descriptive terms in the literature for functionally similar genes. Bioinformatic approaches that use homology-based tools are limited to identifying functionally similar genes based on similarities in their sequences. An effective solution to these limitations is provided by the Gene Ontology (GO), which provides a standardized language to describe gene products from all organisms. The GO comprises three ontologies that enable one to describe the molecular function(s) of gene products, the biological processes to which they contribute, and their cellular locations. Beginning in 2004, the Plant-Associated Microbe Gene Ontology (PAMGO) interest group collaborated with the GO consortium to extend the GO to accommodate terms for describing gene products associated with microbe-host interactions. Currently, over 900 terms that describe biological processes common to diverse plant- and animal-associated microbes are incorporated into the GO database. Here we review some unifying themes common to diverse host-microbe associations and illustrate how the new GO terms facilitate a standardized description of the gene products involved. We also highlight areas where new terms need to be developed, an ongoing process that should involve the whole community.


Subject(s)
Bacterial Physiological Phenomena , Computational Biology/methods , Fungi/physiology , Plants/microbiology , Symbiosis , Animals , Bacteria/genetics , Bacteria/metabolism , Cell Adhesion , Fungi/genetics , Fungi/metabolism , Host-Pathogen Interactions/genetics , Host-Pathogen Interactions/immunology , Plants/immunology , Protein Transport , Symbiosis/genetics , Symbiosis/immunology , Virulence Factors
3.
Trends Microbiol ; 17(7): 262-8, 2009 Jul.
Article in English | MEDLINE | ID: mdl-19577473

ABSTRACT

The ever-increasing number of microbial sequencing projects necessitates a standardized system for the capture of genomic data to ensure that the flood of information produced can be effectively utilized. The Gene Ontology (GO) provides the standard for gene product annotations in the areas of molecular function, biological process and cellular component. A recent effort by the Plant-Associated Microbe Gene Ontology (PAMGO) Consortium has produced more than 800 new GO terms specific for annotating interactions between microbes and their hosts and other symbiotic interactions. In addition, there have been changes and additions to the GO annotation format and evidence storage system to reflect the needs of the microbial annotation community. The capture of annotation information with systems like the GO is absolutely essential to enable the efficient mining of annotation information across diverse genomes and thus to further biological research in meaningful ways.


Subject(s)
Algal Proteins/genetics , Archaeal Proteins/genetics , Bacterial Proteins/genetics , Computational Biology/methods , Computational Biology/standards , Fungal Proteins/genetics , Protozoan Proteins/genetics , Algal Proteins/physiology , Archaeal Proteins/physiology , Bacterial Proteins/physiology , Fungal Proteins/physiology , Protozoan Proteins/physiology , Vocabulary, Controlled
4.
Bioinformatics ; 25(2): 288-9, 2009 Jan 15.
Article in English | MEDLINE | ID: mdl-19033274

ABSTRACT

AmiGO is a web application that allows users to query, browse and visualize ontologies and related gene product annotation (association) data. AmiGO can be used online at the Gene Ontology (GO) website to access the data provided by the GO Consortium; it can also be downloaded and installed to browse local ontologies and annotations. AmiGO is free open source software developed and maintained by the GO Consortium.


Subject(s)
Databases, Genetic , Software , Computational Biology/methods , Information Storage and Retrieval/methods , Internet , User-Computer Interface
5.
Nat Biotechnol ; 25(11): 1251-5, 2007 Nov.
Article in English | MEDLINE | ID: mdl-17989687

ABSTRACT

The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or 'ontologies'. Unfortunately, the very success of this approach has led to a proliferation of ontologies, which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium is pursuing a strategy to overcome this problem. Existing OBO ontologies, including the Gene Ontology, are undergoing coordinated reform, and new ontologies are being created on the basis of an evolving set of shared principles governing ontology development. The result is an expanding family of ontologies designed to be interoperable and logically well formed and to incorporate accurate representations of biological reality. We describe this OBO Foundry initiative and provide guidelines for those who might wish to become involved.


Subject(s)
Information Storage and Retrieval/standards , Terminology as Topic , Vocabulary, Controlled , Humans , Nervous System/anatomy & histology , Nervous System Physiological Phenomena
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