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GeneDive: A gene interaction search and visualization tool to facilitate precision medicine.
Previde, Paul; Thomas, Brook; Wong, Mike; Mallory, Emily K; Petkovic, Dragutin; Altman, Russ B; Kulkarni, Anagha.
Afiliação
  • Previde P; Department of Computer Science, San Francisco State University, San Francisco, California 94132, U.S.A., pprevide@mail.sfsu.edu.
Pac Symp Biocomput ; 23: 590-601, 2018.
Article em En | MEDLINE | ID: mdl-29218917
ABSTRACT
Obtaining relevant information about gene interactions is critical for understanding disease processes and treatment. With the rise in text mining approaches, the volume of such biomedical data is rapidly increasing, thereby creating a new problem for the users of this data information overload. A tool for efficient querying and visualization of biomedical data that helps researchers understand the underlying biological mechanisms for diseases and drug responses, and ultimately helps patients, is sorely needed. To this end we have developed GeneDive, a web-based information retrieval, filtering, and visualization tool for large volumes of gene interaction data. GeneDive offers various features and modalities that guide the user through the search process to efficiently reach the information of their interest. GeneDive currently processes over three million gene-gene interactions with response times within a few seconds. For over half of the curated gene sets sourced from four prominent databases, more than 80% of the gene set members are recovered by GeneDive. In the near future, GeneDive will seamlessly accommodate other interaction types, such as gene-drug and gene-disease interactions, thus enabling full exploration of topics such as precision medicine. The GeneDive application and information about its underlying system architecture are available at http//www.genedive.net.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Epistasia Genética / Medicina de Precisão Limite: Humans Idioma: En Revista: Pac Symp Biocomput Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Epistasia Genética / Medicina de Precisão Limite: Humans Idioma: En Revista: Pac Symp Biocomput Ano de publicação: 2018 Tipo de documento: Article