Hybrid multi-objective and parallel lion optimization algorithm applied to multiple sequence alignment.

O alinhamento múltiplo de sequências é uma tarefa importante na bioinformática,uma vez que pode ser utilizada como base em diferentes análises genômicas. Existem diversas abordagens para a execução de alinhamento múltiplo de sequências, tais como o alinhamento progressivo e os métodos iterativos baseados em metaheurísticas, os quais podem obter bons resultados em um tempo de execução factível. Porém, estas abordagens possuem desvantagens conhecidas na literatura, como a propagação de erros nos alinhamentos progressivos ou resultados em máximo local nos métodos iterativos, como os algoritmos genéticos. A consequência destas desvantagens é que pode-se verificar distorções que afetam negativamente a significância biológica dos alinhamentos múltiplos de sequências obtidos, o que também pode degradar a qualidade das inferências biológicas realizadas. Assim, este trabalho tem o objetivo de modelar e implementar um novo método para alinhamento múltiplo de sequências baseado em um algoritmo híbrido de otimização de leões multiobjetivo e paralelo. Com os resultados obtidos, mostra-se a capacidade do método desenvolvido neste trabalho de obter melhores alinhamentos múltiplos de sequência quando comparados àqueles produzidos por ferramentas do estado-da-arte, como a Kalign, Clustal Omega, MUSCLE e FAMSA.The multiple sequence alignment is an important task in bioinformatics, due to the fact that it is used in different biological analysis. There are many approaches to perform multiple sequence alignments, such as progressive alignment and metaheuristic based methods, such as genetic algorithm, which may produce good results in a feasible execution time. However, these approaches have known disadvantages, such as error propagation on progressive alignment and local optima solutions on genetic algorithm. These disadvantages may cause noises which affect negatively the biological significance of the multiple sequence alignment, which also may affect negatively the biological inferences. Thus, this work aims to model and develop a new method to perform multiple sequence alignments based on a parallel hybrid multi-objective lion optimization algorithm. The obtained results show that the proposed method was able to produce better multiple sequence alignments when compared to those produced by state-of-the-art tools, such as Kalign, Clustal Omega, MUSCLE and FAMSA

Improvements in the sensibility of MSA-GA tool using COFFEE objective function

The sequence alignment is one of the most important tasks in Bioinformatics, playing an important role in the sequences analysis. There are many strategies to perform sequence alignment, since those use deterministic algorithms, as dynamic programming, until those ones, which use heuristic algorithms, as Progressive, Ant Colony (ACO), Genetic Algorithms (GA), Simulated Annealing (SA), among others. In this work, we have implemented the objective function COFFEE in the MSA-GA tool, in substitution of Weighted Sum-of-Pairs (WSP), to improve the final results. In the tests, we were able to verify the approach using COFFEE function achieved better results in 81% of the lower similarity alignments when compared with WSP approach. Moreover, even in the tests with more similar sets, the approach using COFFEE was better in 43% of the times.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Improving risk identification process in project management

Abstract -Nowadays there are many information systems which aim the decision-making, automating the processes of project management. However, many times these systems limit the specific functions related to risk management processes and do not allow the control and effective treatment of uncertain events that may affect the project goals. Thus, this paper proposes the integrated use of the Delphi Technique and Risk Breakdown Structure -RBS in order to contribute to the identification of risks, considering the opportunities and threats in a project, to enhance the beneficial effects of the opportunities and avoid the harmful effects of threats. For the evaluation of the results, it was performed the improvement of a system called System to Aid Project Managing -SAPM, in order to support the automated execution of risk management with an emphasis on risk identification process, since this is a crucial stage for risk management in projects. As a result of this work, it is observed that the combined use of the Delphi Technique and RBS allows the risk identification process can be performed fast and safely through the anonymity of those involved and global visualization of the project

VizieR Online Data Catalog: Gaia DR1 open cluster members (Gaia Collaboration+, 2017)

VizieR On-line Data Catalog: J/A+A/601/A19. Originally published in: 2017A&A...601..A19GWe have determined and examined the astrometric data for 19 open clusters, ranging from the Hyades at just under 47pc to NGC 2422 at nearly 440pc. The clusters are : the Hyades, Coma Berenices, the Pleiades, Praesepe, alpha Per, IC 2391, IC 2602, Blanco 1, NGC 2451, NGC 6475, NGC 7092, NGC 2516, NGC 2232, IC 4665, NGC 6633, Collinder 140, NGC 2422, NGC 3532 and NGC 2547. (2 data files)