David Becerra

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Citizen science games such as Galaxy Zoo, Foldit, and Phylo aim to harness the intelligence and processing power generated by crowds of online gamers to solve scientific problems. However, the selection of the data to be analyzed through these games is under the exclusive control of the game designers, and so are the results produced by gamers. Here, we(More)
BACKGROUND This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A(More)
The problem of finding the Constrained Longest Common Subsequence (CLCS) for three sequences is a problem with many applications. In this paper a novel algorithm to compute the CLCS is proposed. The most important features of the proposed algorithm are: i) This algorithm is able to find a set of possible CLCS solutions instead of simply returning the length(More)
who joined our faculty as an Assistant Professor in August 2008. Becerra earned his Ph.D. at Arizona State University specializing in social policy. Becerra comes to the School with a rich background, initially teaching history to California high school students and eventually directing clinical services offered to children, adolescents, and families in(More)
Finding the Longest Common Subsequence in Weighted Sequences (WLCS) is an important problem in computational biology and bioinformatics. In this paper, we model this problem as a multiobjective optimization problem. As a result, we propose a novel and efficient algorithm that not only finds a WLCS but also the set of all possible solutions. The time(More)