Finding Exact and Solo LTR-Retrotransposons in Biological Sequences Using SVM
Finding repetitive subsequences in genome is a challengeable problem in bioinformatics research area. A lot of approaches have been proposed to solve the problem, which could be divided to library base and de novo methods. The library base methods use predetermined repetitive genome’s subsequences,...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Iranian Institute of Research and Development in Chemical Industries (IRDCI)-ACECR
2012-06-01
|
| Series: | Iranian Journal of Chemistry & Chemical Engineering |
| Subjects: | |
| Online Access: | http://www.ijcce.ac.ir/article_5998_d65726fdbddfb154f4039913065df070.pdf |
| _version_ | 1811276512473645056 |
|---|---|
| author | Hesam Torabi Dashti Ali Masoudi-Nejad Fatemeh Zare |
| author_facet | Hesam Torabi Dashti Ali Masoudi-Nejad Fatemeh Zare |
| author_sort | Hesam Torabi Dashti |
| collection | DOAJ |
| description | Finding repetitive subsequences in genome is a challengeable problem in bioinformatics research area. A lot of approaches have been proposed to solve the problem, which could be divided to library base and de novo methods. The library base methods use predetermined repetitive genome’s subsequences, where library-less methods attempt to discover repetitive subsequences by analytical approaches. In this article we propose novel de novo methodology which stands on theory of pattern recognition’s science. Our methodology by using Support Vector Machine (SVM) classification and clustering methods could extract exact and Solo LTR-retrotransposons. This methodology issued to show complexity efficiency and applicability of the pattern recognition theories in bioinformatics and biomathematics research areas.We demonstrate applicability of our methodology by comparing its results with other well-known de novo method. Both applications return classes of discovered repetitive subsequences, were their results when had applied on show more that 90 percents similarities. |
| first_indexed | 2024-04-12T23:59:08Z |
| format | Article |
| id | doaj.art-580f20f09c81492bb756bbc438162d2b |
| institution | Directory Open Access Journal |
| issn | 1021-9986 1021-9986 |
| language | English |
| last_indexed | 2024-04-12T23:59:08Z |
| publishDate | 2012-06-01 |
| publisher | Iranian Institute of Research and Development in Chemical Industries (IRDCI)-ACECR |
| record_format | Article |
| series | Iranian Journal of Chemistry & Chemical Engineering |
| spelling | doaj.art-580f20f09c81492bb756bbc438162d2b2022-12-22T03:11:24ZengIranian Institute of Research and Development in Chemical Industries (IRDCI)-ACECRIranian Journal of Chemistry & Chemical Engineering1021-99861021-99862012-06-013121111165998Finding Exact and Solo LTR-Retrotransposons in Biological Sequences Using SVMHesam Torabi Dashti0Ali Masoudi-Nejad1Fatemeh Zare2Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics and Center of Excellence in Biomathematics, University of Tehran, Tehran, I.R. IRANLaboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics and Center of Excellence in Biomathematics, University of Tehran, Tehran, I.R. IRANLaboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics and Center of Excellence in Biomathematics, University of Tehran, Tehran, I.R. IRANFinding repetitive subsequences in genome is a challengeable problem in bioinformatics research area. A lot of approaches have been proposed to solve the problem, which could be divided to library base and de novo methods. The library base methods use predetermined repetitive genome’s subsequences, where library-less methods attempt to discover repetitive subsequences by analytical approaches. In this article we propose novel de novo methodology which stands on theory of pattern recognition’s science. Our methodology by using Support Vector Machine (SVM) classification and clustering methods could extract exact and Solo LTR-retrotransposons. This methodology issued to show complexity efficiency and applicability of the pattern recognition theories in bioinformatics and biomathematics research areas.We demonstrate applicability of our methodology by comparing its results with other well-known de novo method. Both applications return classes of discovered repetitive subsequences, were their results when had applied on show more that 90 percents similarities.http://www.ijcce.ac.ir/article_5998_d65726fdbddfb154f4039913065df070.pdfltrsupport vector machinedna repeactrepetitive sequence |
| spellingShingle | Hesam Torabi Dashti Ali Masoudi-Nejad Fatemeh Zare Finding Exact and Solo LTR-Retrotransposons in Biological Sequences Using SVM Iranian Journal of Chemistry & Chemical Engineering ltr support vector machine dna repeact repetitive sequence |
| title | Finding Exact and Solo LTR-Retrotransposons in Biological Sequences Using SVM |
| title_full | Finding Exact and Solo LTR-Retrotransposons in Biological Sequences Using SVM |
| title_fullStr | Finding Exact and Solo LTR-Retrotransposons in Biological Sequences Using SVM |
| title_full_unstemmed | Finding Exact and Solo LTR-Retrotransposons in Biological Sequences Using SVM |
| title_short | Finding Exact and Solo LTR-Retrotransposons in Biological Sequences Using SVM |
| title_sort | finding exact and solo ltr retrotransposons in biological sequences using svm |
| topic | ltr support vector machine dna repeact repetitive sequence |
| url | http://www.ijcce.ac.ir/article_5998_d65726fdbddfb154f4039913065df070.pdf |
| work_keys_str_mv | AT hesamtorabidashti findingexactandsololtrretrotransposonsinbiologicalsequencesusingsvm AT alimasoudinejad findingexactandsololtrretrotransposonsinbiologicalsequencesusingsvm AT fatemehzare findingexactandsololtrretrotransposonsinbiologicalsequencesusingsvm |