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Pedro J Ballester

Showing results (21-30 of 60) with videos related to

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Journal of Chemical Information and Modeling|February 18, 2014
Does a more precise chemical description of protein-ligand complexes lead to more accurate prediction of binding affinity?Pedro J Ballester, Adrian Schreyer, Tom L Blundell
Oncotarget|December 13, 2017
Precision and recall oncology: combining multiple gene mutations for improved identification of drug-sensitive tumoursStefan Naulaerts, Cuong C Dang, Pedro J Ballester
F1000Research|March 30, 2017
Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression dataLinh Nguyen, Cuong C Dang, Pedro J Ballester
Biology Methods & Protocols|November 6, 2024
Graph neural networks are promising for phenotypic virtual screening on cancer cell linesSachin Vishwakarma, Saiveth Hernandez-Hernandez, Pedro J Ballester
Frontiers in Chemistry|May 6, 2016
How Reliable Are Ligand-Centric Methods for Target Fishing?Antonio Peón, Cuong C Dang, Pedro J Ballester
Biomolecules|July 2, 2020
Concise Polygenic Models for Cancer-Specific Identification of Drug-Sensitive Tumors from Their Multi-Omics ProfilesStefan Naulaerts, Michael P Menden, Pedro J Ballester
Journal of Cheminformatics|June 10, 2025
UMAP-based clustering split for rigorous evaluation of AI models for virtual screening on cancer cell linesQianrong Guo, Saiveth Hernandez-Hernandez, Pedro J Ballester
Journal of Molecular Graphics & Modelling|February 4, 2009
Ultrafast shape recognition: evaluating a new ligand-based virtual screening technologyPedro J Ballester, Paul W Finn, W Graham Richards
European Journal of Medicinal Chemistry|August 28, 2014
Biochemical evaluation of virtual screening methods reveals a cell-active inhibitor of the cancer-promoting phosphatases of regenerating liverBirgit Hoeger, Maren Diether, Pedro J Ballester, et al.
Journal of Computer-Aided Molecular Design|February 21, 2014
Prospective virtual screening for novel p53-MDM2 inhibitors using ultrafast shape recognitionSachin P Patil, Pedro J Ballester, Cassidy R Kerezsi
Pageof 6

Showing results (21-30 of 60) with videos related to

Sort By:
Pageof 6
Journal of Chemical Information and Modeling|February 18, 2014
Does a more precise chemical description of protein-ligand complexes lead to more accurate prediction of binding affinity?Pedro J Ballester, Adrian Schreyer, Tom L Blundell
Oncotarget|December 13, 2017
Precision and recall oncology: combining multiple gene mutations for improved identification of drug-sensitive tumoursStefan Naulaerts, Cuong C Dang, Pedro J Ballester
F1000Research|March 30, 2017
Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression dataLinh Nguyen, Cuong C Dang, Pedro J Ballester
Biology Methods & Protocols|November 6, 2024
Graph neural networks are promising for phenotypic virtual screening on cancer cell linesSachin Vishwakarma, Saiveth Hernandez-Hernandez, Pedro J Ballester
Frontiers in Chemistry|May 6, 2016
How Reliable Are Ligand-Centric Methods for Target Fishing?Antonio Peón, Cuong C Dang, Pedro J Ballester
Biomolecules|July 2, 2020
Concise Polygenic Models for Cancer-Specific Identification of Drug-Sensitive Tumors from Their Multi-Omics ProfilesStefan Naulaerts, Michael P Menden, Pedro J Ballester
Journal of Cheminformatics|June 10, 2025
UMAP-based clustering split for rigorous evaluation of AI models for virtual screening on cancer cell linesQianrong Guo, Saiveth Hernandez-Hernandez, Pedro J Ballester
Journal of Molecular Graphics & Modelling|February 4, 2009
Ultrafast shape recognition: evaluating a new ligand-based virtual screening technologyPedro J Ballester, Paul W Finn, W Graham Richards
European Journal of Medicinal Chemistry|August 28, 2014
Biochemical evaluation of virtual screening methods reveals a cell-active inhibitor of the cancer-promoting phosphatases of regenerating liverBirgit Hoeger, Maren Diether, Pedro J Ballester, et al.
Journal of Computer-Aided Molecular Design|February 21, 2014
Prospective virtual screening for novel p53-MDM2 inhibitors using ultrafast shape recognitionSachin P Patil, Pedro J Ballester, Cassidy R Kerezsi
Pageof 6