| Clustering molecular dynamics trajectories for optimizing docking experiments R De Paris, CV Quevedo, DD Ruiz, O Norberto de Souza, RC Barros Computational intelligence and neuroscience 2015 (1), 916240, 2015 | 56 | 2015 |
| WFReDoW: a cloud‐based web environment to handle molecular docking simulations of a fully flexible receptor model R De Paris, FA Frantz, O Norberto de Souza, DDA Ruiz BioMed research international 2013 (1), 469363, 2013 | 36 | 2013 |
| An effective approach for clustering InhA molecular dynamics trajectory using substrate-binding cavity features R De Paris, CV Quevedo, DDA Ruiz, O Norberto de Souza PloS one 10 (7), e0133172, 2015 | 29 | 2015 |
| SmartIX: A database indexing agent based on reinforcement learning G Paludo Licks, J Colleoni Couto, P de Fátima Miehe, R De Paris, ... Applied Intelligence 50, 2575-2588, 2020 | 28 | 2020 |
| A strategic solution to optimize molecular docking simulations using fully-flexible receptor models CV Quevedo, R De Paris, DD Ruiz, ON de Souza Expert Systems with Applications 41 (16), 7608-7620, 2014 | 19 | 2014 |
| A selective method for optimizing ensemble docking-based experiments on an InhA Fully-Flexible receptor model R De Paris, C Vahl Quevedo, DD Ruiz, F Gargano, ON de Souza BMC bioinformatics 19, 1-16, 2018 | 12 | 2018 |
| FReMI: a middleware to handle molecular docking simulations of fully-flexible receptor models in HPC environments R De Paris Pontifícia Universidade Católica do Rio Grande do Sul, 2012 | 8 | 2012 |
| A cloud-based workflow approach for optimizing molecular docking simulations of fully-flexible receptor models and multiple ligands R De Paris, DAD Ruiz, ON De Souza 2015 IEEE 7th International Conference on Cloud Computing Technology and …, 2015 | 4 | 2015 |
| eXplainable Artificial Intelligence on Medical Images: A survey MVS da Silva, RR Arrais, JVS da Silva, FS Tânios, MA Chinelatto, ... arXiv preprint arXiv:2305.07511, 2023 | 2 | 2023 |
| A conceptual many tasks computing architecture to execute molecular docking simulations of a fully-flexible receptor model R De Paris, FA Frantz, O Norberto de Souza, DD Ruiz Advances in Bioinformatics and Computational Biology: 6th Brazilian …, 2011 | 2 | 2011 |
| An effective method to optimize docking-based virtual screening of fully-flexilbe receptor models R De Paris, CV Quevedo, DA Ruiz, O Norberto de Souza 32nd Brazilian Symposium on Databases (SBBD). Minas Gerais: Brazilian …, 2017 | 1 | 2017 |
| Clustering molecular dynamics trajectories with a univariate estimation of distribution algorithm RC Barros, CV Quevedo, R De Paris, MP Basgalupp 2015 IEEE Congress on Evolutionary Computation (CEC), 2058-2065, 2015 | 1 | 2015 |
| Efficient Brazilian Sign Language Recognition: A Study on Mobile Devices VL Fabris, F de Castro Bastos, ACAM de Faria, JVNA da Silva, PA Luiz, ... Iberoamerican Congress on Pattern Recognition, 406-419, 2023 | | 2023 |
| eXplainable Artificial Intelligence on Medical Images: A Survey R Reis Arrais, JV Santos da Silva, F Souza Tânios, MA Chinelatto, ... arXiv e-prints, arXiv: 2305.07511, 2023 | | 2023 |
| An effective method to optimize docking-based virtual screening in a clustered fully-flexible receptor model deployed on cloud platforms R De Paris Pontifícia Universidade Católica do Rio Grande do Sul, 2017 | | 2017 |
| Research Article Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments R De Paris, CV Quevedo, DD Ruiz, ON de Souza, RC Barros | | 2015 |
Duncan Dubugras Alcoba RuizPontifical Catholic University of Rio Grande do Sul - PUCRS - BRAZIL在 pucrs.br 的电子邮件经过验证
