Evaluation of computer methods for biomarker discovery on computational grids
Background: Discovering biomarkers is a fundamental step to understand and deal with genetic diseases. Methods using classic Computer Science algorithms have been adapted in order to support processing large biological data sets, aiming to find useful information to understand causing conditions of...
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Pontificia Universidad Católica de Valparaíso
2013
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oai:scielo:S0717-345820130005000132014-09-17Evaluation of computer methods for biomarker discovery on computational gridsTonini,GustavoSiqueira,Frank feature selection genetics parallel computing pattern detection performance Background: Discovering biomarkers is a fundamental step to understand and deal with genetic diseases. Methods using classic Computer Science algorithms have been adapted in order to support processing large biological data sets, aiming to find useful information to understand causing conditions of diseases such as cancer. Results: This paper describes some promising biomarker discovery methods based on several grid architectures. Each technique has some features that make it more suitable for a particular grid architecture. This matching depends on the parallelizing capabilities of the method and the resource availability in each processing/storage node. Conclusion: The study described in this paper analyzed the performance of biomarker discovery methods in different grid architectures. We find that some methods are more suited for certain grid architectures, resulting in significant performance improvement and producing more accurate results.info:eu-repo/semantics/openAccessPontificia Universidad Católica de ValparaísoElectronic Journal of Biotechnology v.16 n.5 20132013-09-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582013000500013en10.2225/vol16-issue5-fulltext-3 |
| institution |
Scielo Chile |
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Scielo Chile |
| language |
English |
| topic |
feature selection genetics parallel computing pattern detection performance |
| spellingShingle |
feature selection genetics parallel computing pattern detection performance Tonini,Gustavo Siqueira,Frank Evaluation of computer methods for biomarker discovery on computational grids |
| description |
Background: Discovering biomarkers is a fundamental step to understand and deal with genetic diseases. Methods using classic Computer Science algorithms have been adapted in order to support processing large biological data sets, aiming to find useful information to understand causing conditions of diseases such as cancer. Results: This paper describes some promising biomarker discovery methods based on several grid architectures. Each technique has some features that make it more suitable for a particular grid architecture. This matching depends on the parallelizing capabilities of the method and the resource availability in each processing/storage node. Conclusion: The study described in this paper analyzed the performance of biomarker discovery methods in different grid architectures. We find that some methods are more suited for certain grid architectures, resulting in significant performance improvement and producing more accurate results. |
| author |
Tonini,Gustavo Siqueira,Frank |
| author_facet |
Tonini,Gustavo Siqueira,Frank |
| author_sort |
Tonini,Gustavo |
| title |
Evaluation of computer methods for biomarker discovery on computational grids |
| title_short |
Evaluation of computer methods for biomarker discovery on computational grids |
| title_full |
Evaluation of computer methods for biomarker discovery on computational grids |
| title_fullStr |
Evaluation of computer methods for biomarker discovery on computational grids |
| title_full_unstemmed |
Evaluation of computer methods for biomarker discovery on computational grids |
| title_sort |
evaluation of computer methods for biomarker discovery on computational grids |
| publisher |
Pontificia Universidad Católica de Valparaíso |
| publishDate |
2013 |
| url |
http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582013000500013 |
| work_keys_str_mv |
AT toninigustavo evaluationofcomputermethodsforbiomarkerdiscoveryoncomputationalgrids AT siqueirafrank evaluationofcomputermethodsforbiomarkerdiscoveryoncomputationalgrids |
| _version_ |
1718441880989990912 |