A gene wiki for community annotation of gene function.
Ontology highlight
ABSTRACT:
SUBMITTER: Huss JW
PROVIDER: S-EPMC2443188 | biostudies-literature | 2008 Jul
REPOSITORIES: biostudies-literature
Publications
A gene wiki for community annotation of gene function.
Huss Jon W JW Orozco Camilo C Goodale James J Wu Chunlei C Batalov Serge S Vickers Tim J TJ Valafar Faramarz F Su Andrew I AI
PLoS biology 20080701 7
Similar Datasets
Project description:SNPedia (http://www.SNPedia.com) is a wiki resource of the functional consequences of human genetic variation as published in peer-reviewed studies. Online since 2006 and freely available for personal use, SNPedia has focused on the medical, phenotypic and genealogical associations of single nucleotide polymorphisms. Entries are formatted to allow associations to be assigned to single genotypes as well as sets of genotypes (genosets). In this article, we discuss the growth of this resource and its use by affiliated software to create personal genome reports.
| S-EPMC3245045 | biostudies-literature
Project description:Manual annotation of genomic data is extremely valuable to produce an accurate reference gene set but is expensive compared with automatic methods and so has been limited to model organisms. Annotation tools that have been developed at the Wellcome Trust Sanger Institute (WTSI, http://www.sanger.ac.uk/.) are being used to fill that gap, as they can be used remotely and so open up viable community annotation collaborations. We introduce the 'Blessed' annotator and 'Gatekeeper' approach to Community Annotation using the Otterlace/ZMap genome annotation tool. We also describe the strategies adopted for annotation consistency, quality control and viewing of the annotation. DATABASE URL: http://vega.sanger.ac.uk/index.html.
| S-EPMC3308165 | biostudies-literature
Project description:EcoliWiki is the community annotation component of the PortEco (http://porteco.org; formerly EcoliHub) project, an online data resource that integrates information on laboratory strains of Escherichia coli, its phages, plasmids and mobile genetic elements. As one of the early adopters of the wiki approach to model organism databases, EcoliWiki was designed to not only facilitate community-driven sharing of biological knowledge about E. coli as a model organism, but also to be interoperable with other data resources. EcoliWiki content currently covers genes from five laboratory E. coli strains, 21 bacteriophage genomes, F plasmid and eight transposons. EcoliWiki integrates the Mediawiki wiki platform with other open-source software tools and in-house software development to extend how wikis can be used for model organism databases. EcoliWiki can be accessed online at http://ecoliwiki.net.
| S-EPMC3245172 | biostudies-literature
Project description:Saliva has become an attractive body fluid for on-site, remote, and real-time monitoring of oral and systemic health. At the same time, the scientific community needs a saliva-centered information platform that keeps pace with the rapid accumulation of new data and knowledge by annotating, refining, and updating the salivary proteome catalog. We developed the Human Salivary Proteome (HSP) Wiki as a public data platform for researching and retrieving custom-curated data and knowledge on the saliva proteome. The HSP Wiki is dynamically compiled and updated based on published saliva proteome studies and up-to-date protein reference records. It integrates a wide range of available information by funneling in data from established external protein, genome, transcriptome, and glycome databases. In addition, the HSP Wiki incorporates data from human disease-related studies. Users can explore the proteome of saliva simply by browsing the database, querying the available data, performing comparisons of data sets, and annotating existing protein entries using a simple, intuitive interface. The annotation process includes both user feedback and curator committee review to ensure the quality and validity of each entry. Here, we present the first overview of features and functions the HSP Wiki offers. As a saliva proteome-centric, publicly accessible database, the HSP Wiki will advance the knowledge of saliva composition and function in health and disease for users across a wide range of disciplines. As a community-based data- and knowledgebase, the HSP Wiki will serve as a worldwide platform to exchange salivary proteome information, inspire novel research ideas, and foster cross-discipline collaborations. The HSP Wiki will pave the way for harnessing the full potential of the salivary proteome for diagnosis, risk prediction, therapy of oral and systemic diseases, and preparedness for emerging infectious diseases.Database URL: https://salivaryproteome.nidcr.nih.gov/.
| S-EPMC8640339 | biostudies-literature
Project description:BackgroundOntology-based gene annotations are important tools for organizing and analyzing genome-scale biological data. Collecting these annotations is a valuable but costly endeavor. The Gene Wiki makes use of Wikipedia as a low-cost, mass-collaborative platform for assembling text-based gene annotations. The Gene Wiki is comprised of more than 10,000 review articles, each describing one human gene. The goal of this study is to define and assess a computational strategy for translating the text of Gene Wiki articles into ontology-based gene annotations. We specifically explore the generation of structured annotations using the Gene Ontology and the Human Disease Ontology.ResultsOur system produced 2,983 candidate gene annotations using the Disease Ontology and 11,022 candidate annotations using the Gene Ontology from the text of the Gene Wiki. Based on manual evaluations and comparisons to reference annotation sets, we estimate a precision of 90-93% for the Disease Ontology annotations and 48-64% for the Gene Ontology annotations. We further demonstrate that this data set can systematically improve the results from gene set enrichment analyses.ConclusionsThe Gene Wiki is a rapidly growing corpus of text focused on human gene function. Here, we demonstrate that the Gene Wiki can be a powerful resource for generating ontology-based gene annotations. These annotations can be used immediately to improve workflows for building curated gene annotation databases and knowledge-based statistical analyses.
| S-EPMC3271090 | biostudies-literature
Project description:SummaryComputational gene function prediction can serve to focus experimental resources on high-priority experimental tasks. FuncBase is a web resource for viewing quantitative machine learning-based gene function annotations. Quantitative annotations of genes, including fungal and mammalian genes, with Gene Ontology terms are accompanied by a community feedback system. Evidence underlying function annotations is shown. For example, a custom Cytoscape viewer shows functional linkage graphs relevant to the gene or function of interest. FuncBase provides links to external resources, and may be accessed directly or via links from species-specific databases.AvailabilityFuncBase as well as all underlying data and annotations are freely available via http://func.med.harvard.edu/
| S-EPMC2894510 | biostudies-literature
Project description:With the continuous upgrading of high-throughput sequencing technology, a large amount of biological genome data has been deciphered and published. The research on functional genes of biological genomes urgently needs a collection of service websites with user-friendly and full annotation functions for a variety of gene function annotation tools. In this study, iCAZyGFADB, which is a database website integrating nine gene function annotation tools, was perfectly developed to meet the needs of biological genome functional annotation. Its nine gene function annotation tools were Carbohydrate-Active Enzymes (CAZyme) annotation, Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation, Cluster of Orthologous Gene (COG) annotation, Evolutionary Genealogy of Genes: Non-supervised Orthologous Groups (eggNOG) annotation, SwissProt annotation, Pfam annotation, KOG annotation and Animal Transcription Factor DataBase (AnimalTFDB) annotation. It has three advantages. First, it is superior to gene function annotation of other biological cloud analysis platforms and runs very fast. Second, all gene annotation functions of the website are free and open to users. Third, it can annotate eight gene functions (GO, KEGG, COG, eggNOG, SwissProt, Pfam, KOG and AnimalTFDB annotation) of a single species at the same time, while other cloud platforms do not have the ability or need to charge to open for users to complete the annotation of eight gene functions at the same time. Moreover, the development and operation of our database will provide great help for gene function annotation research and significantly improve the efficiency of genome function research and reduce the cost of bioinformatics analysis. Genomic functional annotation researchers can access this database through the following website: http://www.icazygfadb.org.cn/. Database URL: http://www.icazygfadb.org.cn/.
| S-EPMC10684042 | biostudies-literature
Project description:Open biological data are distributed over many resources making them challenging to integrate, to update and to disseminate quickly. Wikidata is a growing, open community database which can serve this purpose and also provides tight integration with Wikipedia. In order to improve the state of biological data, facilitate data management and dissemination, we imported all human and mouse genes, and all human and mouse proteins into Wikidata. In total, 59,721 human genes and 73,355 mouse genes have been imported from NCBI and 27,306 human proteins and 16,728 mouse proteins have been imported from the Swissprot subset of UniProt. As Wikidata is open and can be edited by anybody, our corpus of imported data serves as the starting point for integration of further data by scientists, the Wikidata community and citizen scientists alike. The first use case for these data is to populate Wikipedia Gene Wiki infoboxes directly from Wikidata with the data integrated above. This enables immediate updates of the Gene Wiki infoboxes as soon as the data in Wikidata are modified. Although Gene Wiki pages are currently only on the English language version of Wikipedia, the multilingual nature of Wikidata allows for usage of the data we imported in all 280 different language Wikipedias. Apart from the Gene Wiki infobox use case, a SPARQL endpoint and exporting functionality to several standard formats (e.g. JSON, XML) enable use of the data by scientists. In summary, we created a fully open and extensible data resource for human and mouse molecular biology and biochemistry data. This resource enriches all the Wikipedias with structured information and serves as a new linking hub for the biological semantic web. Database URL: https://www.wikidata.org/.
| S-EPMC4795929 | biostudies-literature
Project description:BackgroundA variety of topic-focused wikis are used in the biomedical sciences to enable the mass-collaborative synthesis and distribution of diverse bodies of knowledge. To address complex problems such as defining the relationships between genes and disease, it is important to bring the knowledge from many different domains together. Here we show how advances in wiki technology and natural language processing can be used to automatically assemble 'meta-wikis' that present integrated views over the data collaboratively created in multiple source wikis.ResultsWe produced a semantic meta-wiki called the Gene Wiki+ that automatically mirrors and integrates data from the Gene Wiki and SNPedia. The Gene Wiki+, available at (http://genewikiplus.org/), captures 8,047 distinct gene-disease relationships. SNPedia accounts for 4,149 of the gene-disease pairs, the Gene Wiki provides 4,377 and only 479 appear independently in both sources. All of this content is available to query and browse and is provided as linked open data.ConclusionsWikis contain increasing amounts of diverse, biological information useful for elucidating the connections between genes and disease. The Gene Wiki+ shows how wiki technology can be used in concert with natural language processing to provide integrated views over diverse underlying data sources.
| S-EPMC3337266 | biostudies-literature
Project description:BackgroundFunctional annotation of bacterial genomes is an obligatory and crucially important step of information processing from the genome sequences into cellular mechanisms. However, there is a lack of computational methods to evaluate the quality of functional assignments.ResultsWe developed a genome-scale model that assigns Bayesian probability to each gene utilizing a known property of functional similarity between neighboring genes in bacteria.ConclusionsOur model clearly distinguished true annotation from random annotation with Bayesian annotation probability >0.95. Our model will provide a useful guide to quantitatively evaluate functional annotation methods and to detect gene sets with reliable annotations.
| S-EPMC5517811 | biostudies-literature