PadMetBio: Parallel and Distributed Metaheuristics for Structural Bioinformatics


Jan/2017 to Dez/2018

Structural bioinformatics deals with problems where the rules that govern the biochemical processes and relations are partially known which makes hard to design efficient computational strategies for these problems. There is a wide range of unanswered questions, which cannot be answered neither by experiments nor by classical modeling and simulation approaches. Specifically, there are several problems that still do not have a computational method that can guarantee a minimum quality of solution. The general goal of this project is to develop metaheuristics models based on robust and scalable parallel and distributed computing for structural bioinformatic problems. International Project (Stic-Amsud 2016) between the Universidade Federal do Rio Grande do Sul (UFRGS, Brasil), Universidad Nacional de San Luis (UNSL, Argentina), Universidad de Santiago de Chile (USACH, Chile), University of Pierre et Marie Currie (UPMC, LIP6, INRIA, França).

Researches:

Meetings:

First meeting - Porto Alegre, Brazil - April 2017:


USACH, UPMC, UNSL and UFRGS, April 2017 in Porto Alegre, Brazil.


Second meeting - Paris, France - December 2017:

USACH, UPMC and UFRGS, December 2017 in Paris, France.

Third meeting - Santiago, Chile - April 2018:

USACH, UPMC, UDP, UTFSM and UFRGS, April 2018 in Santiago, Chile.

Fourth meeting - Porto Alegre, Brazil - December 2018:

USACH and UFRGS, December 2018 in Porto Alegre, Brazil.
Study Missions:

  • Ph.D. Candidate Leonardo de Lima Correa INF/UFRGS/BRAZIL to LIP6/UPMC/FRANCE from Octubre/2018 until September/2019
Publications:


Journals:

  • Solar, R.; Sepulveda, V.; Inostrosa-Psijas, A.; Rojas, O.; Gil-Costa, V. and Marin, M. A Service-Oriented Platform for Approximate Bayesian Computation in Population Genetics. Journal of Computational Biology, ahead of print, 2019.
    DOI: https://doi.org/10.1089/cmb.2018.0217
  • Correa, L.; Borguesan, B.; Farfan, C.; Inostroza-Ponta, M.; Dorn, M. A Memetic Algorithm for 3D Protein Structure Prediction Problem. IEEE-ACM Transactions on Computational Biology and Bioinformatics, v. 15, p. 690-704, 2018.
    DOI: http://dx.doi.org/10.1109/TCBB.2016.2635143
  • Parraga-Alava, J.; Dorn, M.; Inostroza-Ponta, M. A multi-objective gene clustering algorithm guided by apriori biological knowledge with intensification and diversification strategies. BioData Mining, v. 11, p. 1, 2018.
    DOI: http://dx.doi.org/10.1186/s13040-018-0178-4
  • Villalobos-Cid, M.; Ligabue-Braun, R.; Dorn, M; Inostroza-Ponta, M. A memetic algorithm based on an NSGA-II scheme for phylogenetic tree inference. IEEE Transactions on Evolutionary Computation, v. 22, p. 1-1, 2018.
    DOI: http://dx.doi.org/10.1109/tevc.2018.2883888
  • Borguesan, B.; Inostroza-Ponta, M.; Dorn, M. NIAS-Server: Neighbors Influence of Amino acids and Secondary Structures in Proteins. Journal of Computational Biology, v. 24, p. 255-265, 2017.
    DOI: http://dx.doi.org/10.1089/cmb.2016.0074


Proceedings:

  • Borguesan, B.; Narloch, P.H.; Inostroza-Ponta, M.; Dorn, M. A Genetic Algorithm Based on Restricted Tournament Selection for the 3D-PSP Problem. 2018 IEEE Congress on Evolutionary Computation (CEC), 2018, Rio de Janeiro.
    DOI: http://dx.doi.org/10.1109/CEC.2018.8477721
  • Villalobos-Cid, M.; Dorn, M.; Inostroza-Ponta, M. Understanding the Relationship Between Decision and Objective Space in the Multi-Objective Phylogenetic Inference Problem. 2018 IEEE Congress on Evolutionary Computation (CEC), 2018, Rio de Janeiro.
    DOI: http://dx.doi.org/10.1109/CEC.2018.8477689
  • Villalobos-Cid, M.; Dorn, M.; Inostroza-Ponta, M. Performance Comparison of Multi-Objective Local Search Strategies to Infer Phylogenetic Trees. 2018 IEEE Congress on Evolutionary Computation (CEC), 2018, Rio de Janeiro.
    DOI: http://dx.doi.org/10.1109/CEC.2018.8477666
  • Parraga-Alava, J.; Dorn, M.; Inostroza-Ponta, M. Using local search strategies to improve the performance of NSGA-II for the Multi-Criteria Minimum Spanning Tree problem. 2017 IEEE Congress on Evolutionary Computation (CEC), 2018, Donostia.
    DOI: http://dx.doi.org/10.1109/CEC.2017.7969432
  • Correa, L.C.; Inostroza-Ponta, M.; Dorn, M. An evolutionary multi-agent algorithm to explore the high degree of selectivity in three-dimensional protein structures. 2017 IEEE Congress on Evolutionary Computation (CEC), 2018, Donostia.
    DOI: http://dx.doi.org/10.1109/cec.2017.7969431
  • Sepulveda, V.; Solar, R.; Inostrosa, A.; Gil-Costa, V.; Marin, M. Towards Rapid Population Genetics Forward-in-time Simulations. 2017 Winter Simulation Conference, 2017, Las Vegas.
    URL: http://dl.acm.org/citation.cfm?id=3242181.3242410

Finantial Support: