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Omicseq: a web-based search engine for exploring omics datasets.
Sun, Xiaobo; Pittard, William S; Xu, Tianlei; Chen, Li; Zwick, Michael E; Jiang, Xiaoqian; Wang, Fusheng; Qin, Zhaohui S.
Afiliação
  • Sun X; Department of Mathematics and Computer Science, Emory University, 400 Dowman Drive, Atlanta, GA 30322, USA.
  • Pittard WS; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA 30322, USA.
  • Xu T; Department of Mathematics and Computer Science, Emory University, 400 Dowman Drive, Atlanta, GA 30322, USA.
  • Chen L; Department of Mathematics and Computer Science, Emory University, 400 Dowman Drive, Atlanta, GA 30322, USA.
  • Zwick ME; Department of Human Genetics, Emory University School of Medicine, 615 Michael Street, Atlanta, GA 30322, USA.
  • Jiang X; Health Science Department of Biomedical Informatics, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
  • Wang F; Department of Biomedical Informatics, Stony Brook University, HSC L3-043, Stony Brook, NY 11794, USA.
  • Qin ZS; Department of Computer Science, Stony Brook University, Computer Science Building, Stony Brook, NY 11794, USA.
Nucleic Acids Res ; 45(W1): W445-W452, 2017 07 03.
Article em En | MEDLINE | ID: mdl-28402462
ABSTRACT
The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve 'findability' of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http//www.omicseq.org.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Próstata / Interface Usuário-Computador / Neoplasias da Mama / Genômica / Ferramenta de Busca Idioma: En Revista: Nucleic Acids Res Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Próstata / Interface Usuário-Computador / Neoplasias da Mama / Genômica / Ferramenta de Busca Idioma: En Revista: Nucleic Acids Res Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos