Gene prediction by multiple syntenic alignment
Given the increasing number of available genomic sequences, one now faces the task of identifying their functional parts, like the protein coding regions. The gene prediction problem can be addressed in several ways. One of the most promising methods makes use of similarity information between the g...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2005-12-01
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| Series: | Journal of Integrative Bioinformatics |
| Online Access: | https://doi.org/10.1515/jib-2005-13 |
| _version_ | 1818587373649264640 |
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| author | Adi Said S. Ferreira Carlos E. |
| author_facet | Adi Said S. Ferreira Carlos E. |
| author_sort | Adi Said S. |
| collection | DOAJ |
| description | Given the increasing number of available genomic sequences, one now faces the task of identifying their functional parts, like the protein coding regions. The gene prediction problem can be addressed in several ways. One of the most promising methods makes use of similarity information between the genomic DNA and previously annotated sequences (proteins, cDNAs and ESTs). Recently, given the huge amount of newly sequenced genomes, new similarity-based methods are being successfully applied in the task of gene prediction. The so-called comparative-based methods lie in the similarities shared by regions of two evolutionary related genomic sequences. Despite the number of different gene prediction approaches in the literature, this problem remains challenging. In this paper we present a new comparative-based approach to the gene prediction problem. It is based on a syntenic alignment of three or more genomic sequences. With syntenic alignment we mean an alignment that is constructed taking into account the fact that the involved sequences include conserved regions intervened by unconserved ones. We have implemented the proposed algorithm in a computer program and confirm the validity of the approach on a benchmark including triples of human, mouse and rat genomic sequences. |
| first_indexed | 2024-12-16T09:07:50Z |
| format | Article |
| id | doaj.art-4e2acb69bf384e278aaa1817c8801137 |
| institution | Directory Open Access Journal |
| issn | 1613-4516 |
| language | English |
| last_indexed | 2024-12-16T09:07:50Z |
| publishDate | 2005-12-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Journal of Integrative Bioinformatics |
| spelling | doaj.art-4e2acb69bf384e278aaa1817c88011372022-12-21T22:37:02ZengDe GruyterJournal of Integrative Bioinformatics1613-45162005-12-0121384710.1515/jib-2005-13biecoll-jib-2005-13Gene prediction by multiple syntenic alignmentAdi Said S.0Ferreira Carlos E.1Institute of Mathematics and Statistics (IME), University of São Paulo (USP) Rua do Matão 1010 – Cidade Universitária, 05508-900 – São Paulo(SP), BrazilInstitute of Mathematics and Statistics (IME), University of São Paulo (USP) Rua do Matão 1010 - Cidade Universitária, 05508-900 - São Paulo(SP), BrazilGiven the increasing number of available genomic sequences, one now faces the task of identifying their functional parts, like the protein coding regions. The gene prediction problem can be addressed in several ways. One of the most promising methods makes use of similarity information between the genomic DNA and previously annotated sequences (proteins, cDNAs and ESTs). Recently, given the huge amount of newly sequenced genomes, new similarity-based methods are being successfully applied in the task of gene prediction. The so-called comparative-based methods lie in the similarities shared by regions of two evolutionary related genomic sequences. Despite the number of different gene prediction approaches in the literature, this problem remains challenging. In this paper we present a new comparative-based approach to the gene prediction problem. It is based on a syntenic alignment of three or more genomic sequences. With syntenic alignment we mean an alignment that is constructed taking into account the fact that the involved sequences include conserved regions intervened by unconserved ones. We have implemented the proposed algorithm in a computer program and confirm the validity of the approach on a benchmark including triples of human, mouse and rat genomic sequences.https://doi.org/10.1515/jib-2005-13 |
| spellingShingle | Adi Said S. Ferreira Carlos E. Gene prediction by multiple syntenic alignment Journal of Integrative Bioinformatics |
| title | Gene prediction by multiple syntenic alignment |
| title_full | Gene prediction by multiple syntenic alignment |
| title_fullStr | Gene prediction by multiple syntenic alignment |
| title_full_unstemmed | Gene prediction by multiple syntenic alignment |
| title_short | Gene prediction by multiple syntenic alignment |
| title_sort | gene prediction by multiple syntenic alignment |
| url | https://doi.org/10.1515/jib-2005-13 |
| work_keys_str_mv | AT adisaids genepredictionbymultiplesyntenicalignment AT ferreiracarlose genepredictionbymultiplesyntenicalignment |