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Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Dolinski, Kara | - |
dc.contributor.author | Troyanskaya, Olga | - |
dc.date.accessioned | 2021-10-08T19:50:27Z | - |
dc.date.available | 2021-10-08T19:50:27Z | - |
dc.date.issued | 2015 | en_US |
dc.identifier.citation | Dolinski, Kara, and Olga G. Troyanskaya. "Implications of Big Data for cell biology." Molecular Biology of the Cell 26, no. 14 (2015): pp. 2575-2578. doi: 10.1091/mbc.E13-12-0756 | en_US |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/pr13831 | - |
dc.description.abstract | “Big Data” has surpassed “systems biology” and “omics” as the hottest buzzword in the biological sciences, but is there any substance behind the hype? Certainly, we have learned about various aspects of cell and molecular biology from the many individual high-throughput data sets that have been published in the past 15–20 years. These data, although useful as individual data sets, can provide much more knowledge when interrogated with Big Data approaches, such as applying integrative methods that leverage the heterogeneous data compendia in their entirety. Here we discuss the benefits and challenges of such Big Data approaches in biology and how cell and molecular biologists can best take advantage of them. | en_US |
dc.format.extent | 2575 - 2578 | en_US |
dc.language.iso | en_US | en_US |
dc.relation.ispartof | Molecular Biology of the Cell | en_US |
dc.rights | Final published version. Article is made available in OAR by the publisher's permission or policy. | en_US |
dc.title | Implications of Big Data for cell biology | en_US |
dc.type | Journal Article | en_US |
dc.identifier.doi | 10.1091/mbc.E13-12-0756 | - |
dc.identifier.eissn | 1939-4586 | - |
pu.type.symplectic | http://www.symplectic.co.uk/publications/atom-terms/1.0/journal-article | en_US |
Files in This Item:
File | Description | Size | Format | |
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CellBio.pdf | 70.37 kB | Adobe PDF | View/Download |
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