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Dive into the research topics where Amelia Ireland is active.

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Featured researches published by Amelia Ireland.


Nucleic Acids Research | 2004

The Gene Ontology (GO) database and informatics resource.

Midori A. Harris; Jennifer I. Clark; Amelia Ireland; Jane Lomax; Michael Ashburner; R. Foulger; K. Eilbeck; Suzanna E. Lewis; B. Marshall; Christopher J. Mungall; John Richter; Gerald M. Rubin; Judith A. Blake; Mary E. Dolan; Harold J. Drabkin; Janan T. Eppig; David P. Hill; Li Ni; Martin Ringwald; Rama Balakrishnan; J. M. Cherry; Karen R. Christie; Maria C. Costanzo; Selina S. Dwight; Stacia R. Engel; Dianna G. Fisk; Jodi E. Hirschman; Eurie L. Hong; Robert S. Nash; Anand Sethuraman

The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.


Bioinformatics | 2009

AmiGO: online access to ontology and annotation data

Seth Carbon; Amelia Ireland; Christopher J. Mungall; ShengQiang Shu; Brad Marshall; Suzanna E. Lewis

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 Consortium1; it can also be downloaded and installed to browse local ontologies and annotations.2 AmiGO is free open source software developed and maintained by the GO Consortium. Availability: http://amigo.geneontology.org Download: http://sourceforge.net/projects/geneontology/ Contact: [email protected]


Nucleic Acids Research | 2008

The Gene Ontology project in 2008

Midori A. Harris; Jennifer I. Deegan; Amelia Ireland; Jane Lomax; Michael Ashburner; Susan Tweedie; Seth Carbon; Suzanna E. Lewis; Christopher J. Mungall; John Richter; Karen Eilbeck; Judith A. Blake; Alexander D. Diehl; Mary E. Dolan; Harold Drabkin; Janan T. Eppig; David P. Hill; Ni Li; Martin Ringwald; Rama Balakrishnan; Gail Binkley; J. Michael Cherry; Karen R. Christie; Maria C. Costanzo; Qing Dong; Stacia R. Engel; Dianna G. Fisk; Jodi E. Hirschman; Benjamin C. Hitz; Eurie L. Hong

The Gene Ontology (GO) project (http://www.geneontology.org/) provides a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://www.sequenceontology.org/). The ontologies have been extended and refined for several biological areas, and improvements to the structure of the ontologies have been implemented. To improve the quantity and quality of gene product annotations available from its public repository, the GO Consortium has launched a focused effort to provide comprehensive and detailed annotation of orthologous genes across a number of ‘reference’ genomes, including human and several key model organisms. Software developments include two releases of the ontology-editing tool OBO-Edit, and improvements to the AmiGO browser interface.


Journal of Biomedical Informatics | 2011

Cross-product extensions of the Gene Ontology

Christopher J. Mungall; Michael Bada; Tanya Z. Berardini; Jennifer I. Deegan; Amelia Ireland; Midori A. Harris; David P. Hill; Jane Lomax

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.


Microbiology and Molecular Biology Reviews | 2010

Unifying Themes in Microbial Associations with Animal and Plant Hosts Described Using the Gene Ontology

Trudy Torto-Alalibo; Candace W Collmer; Michelle Gwinn-Giglio; Magdalen Lindeberg; Shaowu Meng; Marcus C. Chibucos; Tsai-Tien Tseng; Jane Lomax; Bryan S. Biehl; Amelia Ireland; David McK. Bird; Ralph A. Dean; Jeremy D. Glasner; Nicole T. Perna; João C. Setubal; Alan Collmer; Brett M. Tyler

SUMMARY 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.


Trends in Microbiology | 2009

Applying the Gene Ontology in microbial annotation

Michelle G. Giglio; Candace W Collmer; Jane Lomax; Amelia Ireland

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.


Nature Biotechnology | 2007

The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration

Barry Smith; Michael Ashburner; Cornelius Rosse; Jonathan Bard; William J. Bug; Werner Ceusters; Louis J. Goldberg; Karen Eilbeck; Amelia Ireland; Christopher J. Mungall; Neocles B. Leontis; Philippe Rocca-Serra; Alan Ruttenberg; Susanna-Assunta Sansone; Richard H. Scheuermann; Nigam H. Shah; Patricia L. Whetzel; Suzanna E. Lewis


Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics | 2005

The Gene Ontology project

Midori A. Harris; Jane Lomax; Amelia Ireland; Jennifer I. Clark


Bio-Ontologies 2012 | 2012

Continuous Integration of Open Biological Ontology Libraries

Chris Mungall; Heiko Dietze; Seth Carbon; Amelia Ireland; Sebastian Bauer; Suzanna E. Lewis


Nature Precedings | 2011

Modularization for the Cell Ontology

Christopher J. Mungall; Melissa Haendel; Amelia Ireland; Shahid Manzoor; Terry Meehan; David Osumi-Sutherland; Carlo Torniai; Alexander D. Diehl

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Christopher J. Mungall

Lawrence Berkeley National Laboratory

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Jane Lomax

European Bioinformatics Institute

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Suzanna E. Lewis

Lawrence Berkeley National Laboratory

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Seth Carbon

Lawrence Berkeley National Laboratory

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Jennifer I. Deegan

European Bioinformatics Institute

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Michael Ashburner

European Bioinformatics Institute

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