Automatically extracting functionally equivalent proteins from SwissProt
<p>Abstract</p> <p>Background</p> <p>There is a frequent need to obtain sets of functionally equivalent homologous proteins (FEPs) from different species. While it is usually the case that orthology implies functional equivalence, this is not always true; therefore data...
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| Format: | Article |
| Language: | English |
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BMC
2008-10-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/9/418 |
| _version_ | 1819199573923463168 |
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| author | Martin Andrew CR McMillan Lisa EM |
| author_facet | Martin Andrew CR McMillan Lisa EM |
| author_sort | Martin Andrew CR |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>There is a frequent need to obtain sets of functionally equivalent homologous proteins (FEPs) from different species. While it is usually the case that orthology implies functional equivalence, this is not always true; therefore datasets of orthologous proteins are not appropriate. The information relevant to extracting FEPs is contained in databanks such as UniProtKB/Swiss-Prot and a manual analysis of these data allow FEPs to be extracted on a one-off basis. However there has been no resource allowing the easy, automatic extraction of groups of FEPs – for example, all instances of protein C.</p> <p>We have developed FOSTA, an automatically generated database of FEPs annotated as having the same function in UniProtKB/Swiss-Prot which can be used for large-scale analysis. The method builds a candidate list of homologues and filters out functionally diverged proteins on the basis of functional annotations using a simple text mining approach.</p> <p>Results</p> <p>Large scale evaluation of our FEP extraction method is difficult as there is no gold-standard dataset against which the method can be benchmarked. However, a manual analysis of five protein families confirmed a high level of performance. A more extensive comparison with two manually verified functional equivalence datasets also demonstrated very good performance.</p> <p>Conclusion</p> <p>In summary, FOSTA provides an automated analysis of annotations in UniProtKB/Swiss-Prot to enable groups of proteins already annotated as functionally equivalent, to be extracted. Our results demonstrate that the vast majority of UniProtKB/Swiss-Prot functional annotations are of high quality, and that FOSTA can interpret annotations successfully. Where FOSTA is not successful, we are able to highlight inconsistencies in UniProtKB/Swiss-Prot annotation. Most of these would have presented equal difficulties for manual interpretation of annotations. We discuss limitations and possible future extensions to FOSTA, and recommend changes to the UniProtKB/Swiss-Prot format, which would facilitate text-mining of UniProtKB/Swiss-Prot.</p> |
| first_indexed | 2024-12-23T03:18:30Z |
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| id | doaj.art-15ef1e421bdd48c8b8e5bb235d14f811 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-23T03:18:30Z |
| publishDate | 2008-10-01 |
| publisher | BMC |
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| series | BMC Bioinformatics |
| spelling | doaj.art-15ef1e421bdd48c8b8e5bb235d14f8112022-12-21T18:02:02ZengBMCBMC Bioinformatics1471-21052008-10-019141810.1186/1471-2105-9-418Automatically extracting functionally equivalent proteins from SwissProtMartin Andrew CRMcMillan Lisa EM<p>Abstract</p> <p>Background</p> <p>There is a frequent need to obtain sets of functionally equivalent homologous proteins (FEPs) from different species. While it is usually the case that orthology implies functional equivalence, this is not always true; therefore datasets of orthologous proteins are not appropriate. The information relevant to extracting FEPs is contained in databanks such as UniProtKB/Swiss-Prot and a manual analysis of these data allow FEPs to be extracted on a one-off basis. However there has been no resource allowing the easy, automatic extraction of groups of FEPs – for example, all instances of protein C.</p> <p>We have developed FOSTA, an automatically generated database of FEPs annotated as having the same function in UniProtKB/Swiss-Prot which can be used for large-scale analysis. The method builds a candidate list of homologues and filters out functionally diverged proteins on the basis of functional annotations using a simple text mining approach.</p> <p>Results</p> <p>Large scale evaluation of our FEP extraction method is difficult as there is no gold-standard dataset against which the method can be benchmarked. However, a manual analysis of five protein families confirmed a high level of performance. A more extensive comparison with two manually verified functional equivalence datasets also demonstrated very good performance.</p> <p>Conclusion</p> <p>In summary, FOSTA provides an automated analysis of annotations in UniProtKB/Swiss-Prot to enable groups of proteins already annotated as functionally equivalent, to be extracted. Our results demonstrate that the vast majority of UniProtKB/Swiss-Prot functional annotations are of high quality, and that FOSTA can interpret annotations successfully. Where FOSTA is not successful, we are able to highlight inconsistencies in UniProtKB/Swiss-Prot annotation. Most of these would have presented equal difficulties for manual interpretation of annotations. We discuss limitations and possible future extensions to FOSTA, and recommend changes to the UniProtKB/Swiss-Prot format, which would facilitate text-mining of UniProtKB/Swiss-Prot.</p>http://www.biomedcentral.com/1471-2105/9/418 |
| spellingShingle | Martin Andrew CR McMillan Lisa EM Automatically extracting functionally equivalent proteins from SwissProt BMC Bioinformatics |
| title | Automatically extracting functionally equivalent proteins from SwissProt |
| title_full | Automatically extracting functionally equivalent proteins from SwissProt |
| title_fullStr | Automatically extracting functionally equivalent proteins from SwissProt |
| title_full_unstemmed | Automatically extracting functionally equivalent proteins from SwissProt |
| title_short | Automatically extracting functionally equivalent proteins from SwissProt |
| title_sort | automatically extracting functionally equivalent proteins from swissprot |
| url | http://www.biomedcentral.com/1471-2105/9/418 |
| work_keys_str_mv | AT martinandrewcr automaticallyextractingfunctionallyequivalentproteinsfromswissprot AT mcmillanlisaem automaticallyextractingfunctionallyequivalentproteinsfromswissprot |