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Pedro J Ballester

Showing results (31-40 of 60) with videos related to

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Health Data Science|March 15, 2024
Large-Scale Machine Learning Analysis Reveals DNA Methylation and Gene Expression Response Signatures for Gemcitabine-Treated Pancreatic CancerAdeolu Ogunleye, Chayanit Piyawajanusorn, Ghita Ghislat, et al.
Expert Opinion on Drug Discovery|September 24, 2024
Data-centric challenges with the application and adoption of artificial intelligence for drug discoveryGhita Ghislat, Saiveth Hernandez-Hernandez, Chayanit Piyawajanusorn, et al.
Briefings in Bioinformatics|August 9, 2021
A gentle introduction to understanding preclinical data for cancer pharmaco-omic modelingChayanit Piyawajanusorn, Linh C Nguyen, Ghita Ghislat, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|August 20, 2025
SCORCH2: A Generalized Heterogeneous Consensus Model for High-Enrichment Interaction-Based Virtual ScreeningLin Chen, Vincent Blay, Pedro J Ballester, et al.
BMC Bioinformatics|August 28, 2014
Substituting random forest for multiple linear regression improves binding affinity prediction of scoring functions: Cyscore as a case studyHongjian Li, Kwong-Sak Leung, Man-Hon Wong, et al.
Nature Protocols|October 16, 2023
A practical guide to machine-learning scoring for structure-based virtual screeningViet-Khoa Tran-Nguyen, Muhammad Junaid, Saw Simeon, et al.
Current Research in Structural Biology|June 30, 2022
Structure-based virtual screening for PDL1 dimerizers: Evaluating generic scoring functionsViet-Khoa Tran-Nguyen, Saw Simeon, Muhammad Junaid, et al.
Plos One|January 30, 2014
istar: a web platform for large-scale protein-ligand dockingHongjian Li, Kwong-Sak Leung, Pedro J Ballester, et al.
Wiley Interdisciplinary Reviews. Computational Molecular Science|April 26, 2016
Machine-learning scoring functions to improve structure-based binding affinity prediction and virtual screeningQurrat Ul Ain, Antoniya Aleksandrova, Florian D Roessler, et al.
Molecular Informatics|August 5, 2016
Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data SetsHongjian Li, Kwong-Sak Leung, Man-Hon Wong, et al.
Pageof 6

Showing results (31-40 of 60) with videos related to

Sort By:
Pageof 6
Health Data Science|March 15, 2024
Large-Scale Machine Learning Analysis Reveals DNA Methylation and Gene Expression Response Signatures for Gemcitabine-Treated Pancreatic CancerAdeolu Ogunleye, Chayanit Piyawajanusorn, Ghita Ghislat, et al.
Expert Opinion on Drug Discovery|September 24, 2024
Data-centric challenges with the application and adoption of artificial intelligence for drug discoveryGhita Ghislat, Saiveth Hernandez-Hernandez, Chayanit Piyawajanusorn, et al.
Briefings in Bioinformatics|August 9, 2021
A gentle introduction to understanding preclinical data for cancer pharmaco-omic modelingChayanit Piyawajanusorn, Linh C Nguyen, Ghita Ghislat, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|August 20, 2025
SCORCH2: A Generalized Heterogeneous Consensus Model for High-Enrichment Interaction-Based Virtual ScreeningLin Chen, Vincent Blay, Pedro J Ballester, et al.
BMC Bioinformatics|August 28, 2014
Substituting random forest for multiple linear regression improves binding affinity prediction of scoring functions: Cyscore as a case studyHongjian Li, Kwong-Sak Leung, Man-Hon Wong, et al.
Nature Protocols|October 16, 2023
A practical guide to machine-learning scoring for structure-based virtual screeningViet-Khoa Tran-Nguyen, Muhammad Junaid, Saw Simeon, et al.
Current Research in Structural Biology|June 30, 2022
Structure-based virtual screening for PDL1 dimerizers: Evaluating generic scoring functionsViet-Khoa Tran-Nguyen, Saw Simeon, Muhammad Junaid, et al.
Plos One|January 30, 2014
istar: a web platform for large-scale protein-ligand dockingHongjian Li, Kwong-Sak Leung, Pedro J Ballester, et al.
Wiley Interdisciplinary Reviews. Computational Molecular Science|April 26, 2016
Machine-learning scoring functions to improve structure-based binding affinity prediction and virtual screeningQurrat Ul Ain, Antoniya Aleksandrova, Florian D Roessler, et al.
Molecular Informatics|August 5, 2016
Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data SetsHongjian Li, Kwong-Sak Leung, Man-Hon Wong, et al.
Pageof 6