GeNets: a unified web platform for network-based genomic analyses
Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We pre...
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| Format: | Article |
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Nature Publishing Group
2018
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| Online Access: | http://hdl.handle.net/1721.1/116783 https://orcid.org/0000-0001-8567-2049 |
| _version_ | 1826200750000177152 |
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| author | Li, Taibo Kim, April Rosenbluh, Joseph Horn, Heiko Greenfeld, Liraz An, David Zimmer, Andrew Liberzon, Arthur Bistline, Jon Natoli, Ted Li, Yang Tsherniak, Aviad Narayan, Rajiv Subramanian, Aravind Liefeld, Ted Wong, Bang Thompson, Dawn Calvo, Sarah Carr, Steve Boehm, Jesse Jaffe, Jake Mesirov, Jill Hacohen, Nir Regev, Aviv Lage, Kasper |
| author2 | Massachusetts Institute of Technology. Department of Biology |
| author_facet | Massachusetts Institute of Technology. Department of Biology Li, Taibo Kim, April Rosenbluh, Joseph Horn, Heiko Greenfeld, Liraz An, David Zimmer, Andrew Liberzon, Arthur Bistline, Jon Natoli, Ted Li, Yang Tsherniak, Aviad Narayan, Rajiv Subramanian, Aravind Liefeld, Ted Wong, Bang Thompson, Dawn Calvo, Sarah Carr, Steve Boehm, Jesse Jaffe, Jake Mesirov, Jill Hacohen, Nir Regev, Aviv Lage, Kasper |
| author_sort | Li, Taibo |
| collection | MIT |
| description | Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets. |
| first_indexed | 2024-09-23T11:41:10Z |
| format | Article |
| id | mit-1721.1/116783 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:41:10Z |
| publishDate | 2018 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/1167832022-10-01T05:16:41Z GeNets: a unified web platform for network-based genomic analyses Li, Taibo Kim, April Rosenbluh, Joseph Horn, Heiko Greenfeld, Liraz An, David Zimmer, Andrew Liberzon, Arthur Bistline, Jon Natoli, Ted Li, Yang Tsherniak, Aviad Narayan, Rajiv Subramanian, Aravind Liefeld, Ted Wong, Bang Thompson, Dawn Calvo, Sarah Carr, Steve Boehm, Jesse Jaffe, Jake Mesirov, Jill Hacohen, Nir Regev, Aviv Lage, Kasper Massachusetts Institute of Technology. Department of Biology Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Li, Taibo Regev, Aviv Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets. 2018-07-05T13:38:42Z 2018-07-05T13:38:42Z 2018-06 2018-05 2018-07-03T14:06:13Z Article http://purl.org/eprint/type/JournalArticle 1548-7091 1548-7105 http://hdl.handle.net/1721.1/116783 Li, Taibo et al. “GeNets: a Unified Web Platform for Network-Based Genomic Analyses.” Nature Methods 15, 7 (June 2018): 543–546 © 2018 The Author(s) https://orcid.org/0000-0001-8567-2049 http://dx.doi.org/10.1038/s41592-018-0039-6 Nature Methods Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Nature Publishing Group bioRxiv |
| spellingShingle | Li, Taibo Kim, April Rosenbluh, Joseph Horn, Heiko Greenfeld, Liraz An, David Zimmer, Andrew Liberzon, Arthur Bistline, Jon Natoli, Ted Li, Yang Tsherniak, Aviad Narayan, Rajiv Subramanian, Aravind Liefeld, Ted Wong, Bang Thompson, Dawn Calvo, Sarah Carr, Steve Boehm, Jesse Jaffe, Jake Mesirov, Jill Hacohen, Nir Regev, Aviv Lage, Kasper GeNets: a unified web platform for network-based genomic analyses |
| title | GeNets: a unified web platform for network-based genomic analyses |
| title_full | GeNets: a unified web platform for network-based genomic analyses |
| title_fullStr | GeNets: a unified web platform for network-based genomic analyses |
| title_full_unstemmed | GeNets: a unified web platform for network-based genomic analyses |
| title_short | GeNets: a unified web platform for network-based genomic analyses |
| title_sort | genets a unified web platform for network based genomic analyses |
| url | http://hdl.handle.net/1721.1/116783 https://orcid.org/0000-0001-8567-2049 |
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