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Christian Vahl Quevedo
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2010 – 2019
- 2018
- [j3]Renata De Paris, Christian Vahl Quevedo, Duncan D. Ruiz
, Furia Gargano, Osmar Norberto de Souza
A selective method for optimizing ensemble docking-based experiments on an InhA Fully-Flexible receptor model. BMC Bioinform. 19(1): 235:1-235:16 (2018) - 2016
- [b1]Christian Vahl Quevedo:
Triagem virtual em banco de dados de ligantes considerando propriedades físico-químicas de um modelo de receptor totalmente flexível. Pontifícia Universidade Católica do Rio Grande do Sul, Brazil, 2016 - [c3]Henry E. L. Cagnini
Medoid-based data clustering with estimation of distribution algorithms. SAC 2016: 112-115 - 2015
- [j2]Renata De Paris, Christian Vahl Quevedo, Duncan Dubugras A. Ruiz
Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments. Comput. Intell. Neurosci. 2015: 916240:1-916240:9 (2015) - [c2]Rodrigo C. Barros
Clustering Molecular Dynamics Trajectories with a univariate estimation of distribution algorithm. CEC 2015: 2058-2065 - 2014
- [j1]Christian Vahl Quevedo, Renata De Paris, Duncan D. Ruiz
A strategic solution to optimize molecular docking simulations using Fully-Flexible Receptor models. Expert Syst. Appl. 41(16): 7608-7620 (2014) - 2012
- [c1]Ana T. Winck, Christian Vahl Quevedo, Karina S. Machado
A Comparative Analysis of Public Ligand Databases Based on Molecular Descriptors. BSB 2012: 156-167
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