A field guide to cultivating computational biology
Biomedical research centers can empower basic discovery and novel therapeutic strategies by leveraging their large-scale datasets from experiments and patients. This data, together with new technologies to create and analyze it, has ushered in an era of data-driven discovery which requires moving be...
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| Veröffentlicht in: | arXiv.org 2021-04 |
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| creator | Carpenter, Anne E Greene, Casey S Carnici, Piero Carvalho, Benilton S de Hoon, Michiel Finley, Stacey Kim-Anh Le Cao Jerry SH Lee Marchionni, Luigi Sindi, Suzanne Theis, Fabian J Way, Gregory P Yang, Jean YH Fertig, Elana J |
| description | Biomedical research centers can empower basic discovery and novel therapeutic strategies by leveraging their large-scale datasets from experiments and patients. This data, together with new technologies to create and analyze it, has ushered in an era of data-driven discovery which requires moving beyond the traditional individual, single-discipline investigator research model. This interdisciplinary niche is where computational biology thrives. It has matured over the past three decades and made major contributions to scientific knowledge and human health, yet researchers in the field often languish in career advancement, publication, and grant review. We propose solutions for individual scientists, institutions, journal publishers, funding agencies, and educators. |
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| identifier | EISSN: 2331-8422 |
| ispartof | arXiv.org, 2021-04 |
| issn | 2331-8422 |
| language | eng |
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| source | Free E- Journals |
| subjects | Biology New technology Research facilities |
| title | A field guide to cultivating computational biology |
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