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Improving the performance of Transposable Elements detection tools

Loureiro, Tiago ; Camacho, Rui ; Vieira, Jorge ; Fonseca, Nuno A.

Journal of Integrative Bioinformatics - JIB (ISSN 1613-4516)


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Abstract:
Transposable Elements (TE) are sequences of DNA that move and transpose within a genome. TEs, as mutation agents, are quite important for their role in both genome alteration diseases and on species evolution. Several tools have been developed to discover and annotate TEs but no single tool achieves good results on all different types of TEs. In this paper we evaluate the performance of several TEs detection and annotation tools and investigate if Machine Learning techniques can be used to improve their overall detection accuracy. The results of an in silico evaluation of TEs detection and annotation tools indicate that their performance can be improved by using machine learning constructed classifiers.


Institution: Faculty of Technology, Research Groups in Informatics
DDC classification: Data processing, computer science, computer systems

Suggested Citation:
Loureiro, Tiago ; Camacho, Rui ; Vieira, Jorge ; Fonseca, Nuno A.  (2013)  Improving the performance of Transposable Elements detection tools. Journal of Integrative Bioinformatics - JIB (ISSN 1613-4516), 10(3): Special Issue: Selected extended papers of the 7th International Conference on Practical Applications of Computational Biology and Bioinformatics, Salamanca, Spain, 2013

Online-Journal: http://journal.imbio.de/article.php?aid=231
URL: http://biecoll.ub.uni-bielefeld.de/volltexte/2013/5309



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