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Bioinformatics Tools for Extracellular Vesicles Research.
Keerthikumar, Shivakumar; Gangoda, Lahiru; Gho, Yong Song; Mathivanan, Suresh.
Afiliação
  • Keerthikumar S; Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, LIMS1, Bundoora, Melbourne, VIC, 3086, Australia.
  • Gangoda L; Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, LIMS1, Bundoora, Melbourne, VIC, 3086, Australia.
  • Gho YS; Department of Life Sciences, Pohang University of Science and Technology, Pohang, 790-784, Republic of Korea.
  • Mathivanan S; Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, LIMS1, Bundoora, Melbourne, VIC, 3086, Australia. S.Mathivanan@latrobe.edu.au.
Methods Mol Biol ; 1545: 189-196, 2017.
Article em En | MEDLINE | ID: mdl-27943215
ABSTRACT
Extracellular vesicles (EVs) are a class of membranous vesicles that are released by multiple cell types into the extracellular environment. This unique class of extracellular organelles which play pivotal role in intercellular communication are conserved across prokaryotes and eukaryotes. Depending upon the cell origin and the functional state, the molecular cargo including proteins, lipids, and RNA within the EVs are modulated. Owing to this, EVs are considered as a subrepertoire of the host cell and are rich reservoirs of disease biomarkers. In addition, the availability of EVs in multiple bodily fluids including blood has created significant interest in biomarker and signaling research. With the advancement in high-throughput techniques, multiple EV studies have embarked on profiling the molecular cargo. To benefit the scientific community, existing free Web-based resources including ExoCarta, EVpedia, and Vesiclepedia catalog multiple datasets. These resources aid in elucidating molecular mechanism and pathophysiology underlying different disease conditions from which EVs are isolated. Here, the existing bioinformatics tools to perform integrated analysis to identify key functional components in the EV datasets are discussed.
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Base de dados: MEDLINE Assunto principal: Pesquisa / Biologia Computacional / Vesículas Extracelulares Idioma: En Ano de publicação: 2017 Tipo de documento: Article
Buscar no Google
Base de dados: MEDLINE Assunto principal: Pesquisa / Biologia Computacional / Vesículas Extracelulares Idioma: En Ano de publicação: 2017 Tipo de documento: Article