| Fast and flexible protein design using deep graph neural networks A Strokach, D Becerra, C Corbi-Verge, A Perez-Riba, PM Kim Cell systems 11 (4), 402-411. e4, 2020 | 310 | 2020 |
| Open-Phylo: a customizable crowd-computing platform for multiple sequence alignment D Kwak, A Kam, D Becerra, Q Zhou, A Hops, E Zarour, A Kam, ... Genome biology 14 (10), R116, 2013 | 47 | 2013 |
| A parallel multi-objective ab initio approach for protein structure prediction D Becerra, A Sandoval, D Restrepo-Montoya, FN Luis 2010 IEEE international conference on bioinformatics and biomedicine (BIBM …, 2010 | 32 | 2010 |
| Fast and flexible design of novel proteins using graph neural networks A Strokach, D Becerra, C Corbi-Verge, A Perez-Riba, PM Kim BioRxiv, 868935, 2019 | 21 | 2019 |
| A novel ab-initio genetic-based approach for protein folding prediction SRD Torres, DCB Romero, LFN Vasquez, YJP Ardila Proceedings of the 9th annual conference on Genetic and evolutionary …, 2007 | 21 | 2007 |
| A multi-objective evolutionary algorithm for improving multiple sequence alignments W Soto, D Becerra Brazilian Symposium on Bioinformatics, 73-82, 2014 | 20 | 2014 |
| RNAmigos2: accelerated structure-based RNA virtual screening with deep graph learning JG Carvajal-Patiño, V Mallet, D Becerra, LF Niño Vasquez, C Oliver, ... Nature Communications 16 (1), 1-12, 2025 | 19 | 2025 |
| A multi-objective optimization energy approach to predict the ligand conformation in a docking process A Sandoval-Perez, D Becerra, D Vanegas, D Restrepo-Montoya, F Nino European Conference on Genetic Programming, 181-192, 2013 | 18 | 2013 |
| Identification of Plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models D Restrepo-Montoya, D Becerra, JG Carvajal-Patiño, A Mongui, LF Niño, ... PLoS One 6 (10), e25189, 2011 | 16 | 2011 |
| Adherencia al control prenatal en la Clínica de Gestantes Adolescentes del Hospital de Engativá de Bogota C Villacis, D Becerra, L Negrete Universidad nacional de colombia. Recuperado de http://www. bdigital. unal …, 2012 | 10 | 2012 |
| Fast and flexible protein design using deep graph neural networks. Cell Syst 11: 402-411. e4 A Strokach, D Becerra, C Corbi-Verge, A Perez-Riba, PM Kim | 8 | 2020 |
| A Method to Calculate the Relative Binding Free Energy Differences of α-Helical Stapled Peptides PA Valiente, D Becerra, PM Kim The Journal of Organic Chemistry 85 (3), 1644-1651, 2020 | 8 | 2020 |
| An association rule based approach for biological sequence feature classification D Becerra, D Vanegas, G Cantor, L Nino 2009 IEEE Congress on Evolutionary Computation, 3111-3118, 2009 | 8 | 2009 |
| Un modelo de asignación de recursos a rutas en el sistema de transporte masivo TransMilenio S Duarte, D Becerra, LF Niño Revista Avances en Sistemas e Informática 5 (1), 163-171, 2008 | 8 | 2008 |
| Fast and flexible coarse-grained prediction of protein folding routes using ensemble modeling and evolutionary sequence variation D Becerra, A Butyaev, J Waldispühl Bioinformatics 36 (5), 1420-1428, 2020 | 7 | 2020 |
| A parallel framework for multi-objective evolutionary optimization D Dasgupta, D Becerra, A Banceanu, F Nino, J Simien IEEE Congress on Evolutionary Computation, 1-8, 2010 | 7 | 2010 |
| An algorithm for constrained LCS D Becerra, W Soto, L Nino, Y Pinzón ACS/IEEE International Conference on Computer Systems and Applications …, 2010 | 7 | 2010 |
| Computational generation of proteins with predetermined three-dimensional shapes using ProteinSolver A Strokach, D Becerra, C Corbi-Verge, A Perez-Riba, PM Kim STAR protocols 2 (2), 100505, 2021 | 5 | 2021 |
| Fast and flexible protein design using deep graph neural networks. Cell Syst 11 (4): 402–411 A Strokach, D Becerra, C Corbi-Verge, A Perez-Riba, PM Kim | 5 | 2020 |
| Fast and Flexible Protein Design Using Deep Graph Neural Networks. Cell Systems. 2020; 11 (4): 402–411. e4 A Strokach, D Becerra, C Corbi-Verge, A Perez-Riba, PM Kim | 5 | |
