Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput <i>Omics</i> Datasets.

Ramos, Pablo Ivan Pereira; Arge, Luis Willian Pacheco; Lima, Nicholas Costa Barroso; Fukutani, Kiyoshi F; de Queiroz, Artur Trancoso L

Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets.

Ramos, Pablo Ivan Pereira; Arge, Luis Willian Pacheco; Lima, Nicholas Costa Barroso; Fukutani, Kiyoshi F; de Queiroz, Artur Trancoso L.

Afiliación

Ramos PIP; Center for Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil.
Arge LWP; Laboratório de Genética Molecular e Biotecnologia Vegetal, Centro de Ciências da Saúde, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
Lima NCB; Departamento de Bioquímica e Biologia Molecular, Universidade Federal do Ceará, Fortaleza, Brazil.
Fukutani KF; Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Fundação José Silveira, Salvador, Brazil.
de Queiroz ATL; Center for Data and Knowledge Integration for Health (CIDACS), Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil.

Front Genet ; 10: 1120, 2019.

Article en En | MEDLINE | ID: mdl-31798629

Palabras clave

correlation networks; graph; high-throughput sequencing; network analysis; omics; proteinprotein interaction; regulatory networks; systems biology

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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Front Genet Año: 2019 Tipo del documento: Article País de afiliación: Brasil

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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Front Genet Año: 2019 Tipo del documento: Article País de afiliación: Brasil