Parameters Optimization in Entropic Segmentation Processes for the Analysis of Genetic Sequences

Autor:	Cristhy Jimenez, Pablo Lozada, Tomás Arredondo
Rok vydání:	2014
Předmět:	Sequence Iterative and incremental development business.industry Computer science Process (computing) Value (computer science) Pattern recognition Bioinformatics Position (vector) Segmentation Artificial intelligence Sensitivity (control systems) Divergence (statistics) business
Zdroj:	ITNG
DOI:	10.1109/itng.2014.76
Popis:	Csiszar's divergence measures are commonly applied in the analysis of genetic sequences. The establishing of segment size and threshold values can help to improve the entropic segmentation process. This paper describes the development of an optimization methodology for the entropic segmentation process, based in the discovering of the optimum segment size and threshold values. An iterative process was applied to the four serotypes of Dengue virus in order to identify the proteins position within each serotype. The obtained results showed that it is possible to establish parameters for discriminating the divergence measures values and also improve the sensitivity value when a protein is localized in the sequence.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::cd17d84052ecb730149f8cd9f2ca6e3d https://doi.org/10.1109/itng.2014.76 Zobrazit plný text záznamu