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1.
PLoS Comput Biol ; 17(10): e1009463, 2021 10.
Artigo em Inglês | MEDLINE | ID: mdl-34710081

RESUMO

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills.


Assuntos
Crowdsourcing/métodos , Ontologia Genética , Anotação de Sequência Molecular/métodos , Biologia Computacional , Bases de Dados Genéticas , Humanos , Proteínas/genética , Proteínas/fisiologia
2.
Nucleic Acids Res ; 42(Database issue): D677-84, 2014 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-24285306

RESUMO

PortEco (http://porteco.org) aims to collect, curate and provide data and analysis tools to support basic biological research in Escherichia coli (and eventually other bacterial systems). PortEco is implemented as a 'virtual' model organism database that provides a single unified interface to the user, while integrating information from a variety of sources. The main focus of PortEco is to enable broad use of the growing number of high-throughput experiments available for E. coli, and to leverage community annotation through the EcoliWiki and GONUTS systems. Currently, PortEco includes curated data from hundreds of genome-wide RNA expression studies, from high-throughput phenotyping of single-gene knockouts under hundreds of annotated conditions, from chromatin immunoprecipitation experiments for tens of different DNA-binding factors and from ribosome profiling experiments that yield insights into protein expression. Conditions have been annotated with a consistent vocabulary, and data have been consistently normalized to enable users to find, compare and interpret relevant experiments. PortEco includes tools for data analysis, including clustering, enrichment analysis and exploration via genome browsers. PortEco search and data analysis tools are extensively linked to the curated gene, metabolic pathway and regulation content at its sister site, EcoCyc.


Assuntos
Bases de Dados Genéticas , Escherichia coli/genética , Alelos , Proteínas de Ligação a DNA/metabolismo , Escherichia coli/metabolismo , Proteínas de Escherichia coli/metabolismo , Genes Bacterianos , Genoma Bacteriano , Sequenciamento de Nucleotídeos em Larga Escala , Internet , Fenótipo , RNA Mensageiro/metabolismo , Ribossomos/metabolismo , Software
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