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Algorithms 2017, 10(2), 36; doi:10.3390/a10020036

DNA Paired Fragment Assembly Using Graph Theory

1
Physics and Mathematics, Universidad Iberoamericana Ciudad de México, Prolongación Paseo de la Reforma 880, Lomas de Santa Fe, Ciudad de México 01219, Mexico
2
Engineering Department, Universidad Iberoamericana Ciudad de México, Prolongación Paseo de la Reforma 880, Lomas de Santa Fe, Ciudad de México 01219, Mexico
3
Physics and Mathematics Department, Universidad Iberoamericana Ciudad de México, Prolongación Paseo de la Reforma 880, Lomas de Santa Fe, Ciudad de México 01219, Mexico
*
Author to whom correspondence should be addressed.
Academic Editor: Andras Farago
Received: 26 January 2017 / Revised: 27 February 2017 / Accepted: 17 March 2017 / Published: 24 March 2017
(This article belongs to the Special Issue Networks, Communication, and Computing)
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Abstract

DNA fragment assembly requirements have generated an important computational problem created by their structure and the volume of data. Therefore, it is important to develop algorithms able to produce high-quality information that use computer resources efficiently. Such an algorithm, using graph theory, is introduced in the present article. We first determine the overlaps between DNA fragments, obtaining the edges of a directed graph; with this information, the next step is to construct an adjacency list with some particularities. Using the adjacency list, it is possible to obtain the DNA contigs (group of assembled fragments building a contiguous element) using graph theory. We performed a set of experiments on real DNA data and compared our results to those obtained with common assemblers (Edena and Velvet). Finally, we searched the contigs in the original genome, in our results and in those of Edena and Velvet. View Full-Text
Keywords: DNA fragment assembly; Trie data structure; graph theory algorithms DNA fragment assembly; Trie data structure; graph theory algorithms
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Quiroz-Ibarra, J.E.; Mallén-Fullerton, G.M.; Fernández-Anaya, G. DNA Paired Fragment Assembly Using Graph Theory. Algorithms 2017, 10, 36.

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