IsoBase: a database of functionally related proteins across PPI networks
We describe IsoBase, a database identifying functionally related proteins, across five major eukaryotic model organisms: Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus and Homo Sapiens. Nearly all existing algorithms for orthology detection are based on seque...
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| Format: | Article |
| Language: | en_US |
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Oxford University Press
2012
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| Online Access: | http://hdl.handle.net/1721.1/70134 https://orcid.org/0000-0003-1303-5598 https://orcid.org/0000-0002-2724-7228 |
| _version_ | 1826204510781964288 |
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| author | Park, Daniel Kyu Singh, Rohit Baym, Michael Hartmann Liao, Chung-Shou Berger, Bonnie |
| author2 | Massachusetts Institute of Technology. Computational and Systems Biology Program |
| author_facet | Massachusetts Institute of Technology. Computational and Systems Biology Program Park, Daniel Kyu Singh, Rohit Baym, Michael Hartmann Liao, Chung-Shou Berger, Bonnie |
| author_sort | Park, Daniel Kyu |
| collection | MIT |
| description | We describe IsoBase, a database identifying functionally related proteins, across five major eukaryotic model organisms: Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus and Homo Sapiens. Nearly all existing algorithms for orthology detection are based on sequence comparison. Although these have been successful in orthology prediction to some extent, we seek to go beyond these methods by the integration of sequence data and protein–protein interaction (PPI) networks to help in identifying true functionally related proteins. With that motivation, we introduce IsoBase, the first publicly available ortholog database that focuses on functionally related proteins. The groupings were computed using the IsoRankN algorithm that uses spectral methods to combine sequence and PPI data and produce clusters of functionally related proteins. These clusters compare favorably with those from existing approaches: proteins within an IsoBase cluster are more likely to share similar Gene Ontology (GO) annotation. A total of 48 120 proteins were clustered into 12 693 functionally related groups. The IsoBase database may be browsed for functionally related proteins across two or more species and may also be queried by accession numbers, species-specific identifiers, gene name or keyword. The database is freely available for download at http://isobase.csail.mit.edu/. |
| first_indexed | 2024-09-23T12:56:26Z |
| format | Article |
| id | mit-1721.1/70134 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:56:26Z |
| publishDate | 2012 |
| publisher | Oxford University Press |
| record_format | dspace |
| spelling | mit-1721.1/701342022-09-28T11:00:41Z IsoBase: a database of functionally related proteins across PPI networks Park, Daniel Kyu Singh, Rohit Baym, Michael Hartmann Liao, Chung-Shou Berger, Bonnie Massachusetts Institute of Technology. Computational and Systems Biology Program Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Department of Mathematics Berger, Bonnie Singh, Rohit Baym, Michael Hartmann Park, Daniel Kyu Berger, Bonnie We describe IsoBase, a database identifying functionally related proteins, across five major eukaryotic model organisms: Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus and Homo Sapiens. Nearly all existing algorithms for orthology detection are based on sequence comparison. Although these have been successful in orthology prediction to some extent, we seek to go beyond these methods by the integration of sequence data and protein–protein interaction (PPI) networks to help in identifying true functionally related proteins. With that motivation, we introduce IsoBase, the first publicly available ortholog database that focuses on functionally related proteins. The groupings were computed using the IsoRankN algorithm that uses spectral methods to combine sequence and PPI data and produce clusters of functionally related proteins. These clusters compare favorably with those from existing approaches: proteins within an IsoBase cluster are more likely to share similar Gene Ontology (GO) annotation. A total of 48 120 proteins were clustered into 12 693 functionally related groups. The IsoBase database may be browsed for functionally related proteins across two or more species and may also be queried by accession numbers, species-specific identifiers, gene name or keyword. The database is freely available for download at http://isobase.csail.mit.edu/. National Institute of General Medical Sciences (U.S.) (Grant Number 1R01GM081871) Fannie and John Hertz Foundation National Science Foundation (U.S.) (NSF MSPRF) National Science Council of Taiwan (NSC99-2218-E-007-010) National Institutes of Health (U.S.) (1R01GM081871) 2012-04-25T19:20:03Z 2012-04-25T19:20:03Z 2011-01 2010-10 Article http://purl.org/eprint/type/JournalArticle 0305-1048 1362-4962 http://hdl.handle.net/1721.1/70134 Park, D. et al. “IsoBase: a Database of Functionally Related Proteins Across PPI Networks.” Nucleic Acids Research 39.Database (2010): D295–D300. Web. https://orcid.org/0000-0003-1303-5598 https://orcid.org/0000-0002-2724-7228 en_US http://dx.doi.org/10.1093/nar/gkq1234 Nucleic Acids Research Creative Commons Attribution Non-Commercial License http://creativecommons.org/licenses/ by-nc/2.5 application/pdf Oxford University Press Oxford University Press |
| spellingShingle | Park, Daniel Kyu Singh, Rohit Baym, Michael Hartmann Liao, Chung-Shou Berger, Bonnie IsoBase: a database of functionally related proteins across PPI networks |
| title | IsoBase: a database of functionally related proteins across PPI networks |
| title_full | IsoBase: a database of functionally related proteins across PPI networks |
| title_fullStr | IsoBase: a database of functionally related proteins across PPI networks |
| title_full_unstemmed | IsoBase: a database of functionally related proteins across PPI networks |
| title_short | IsoBase: a database of functionally related proteins across PPI networks |
| title_sort | isobase a database of functionally related proteins across ppi networks |
| url | http://hdl.handle.net/1721.1/70134 https://orcid.org/0000-0003-1303-5598 https://orcid.org/0000-0002-2724-7228 |
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