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Methods in Molecular Biology (Clifton, N.J.)
|
August 28, 2019
Building Machine-Learning Scoring Functions for Structure-Based Prediction of Intermolecular Binding Affinity
Maciej Wójcikowski, Pawel Siedlecki, Pedro J Ballester
Bioinformatics (Oxford, England)
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March 19, 2010
A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking
Pedro J Ballester, John B O Mitchell
Scientific Reports
|
June 21, 2017
Predicting the Reliability of Drug-target Interaction Predictions with Maximum Coverage of Target Space
Antonio Peón, Stefan Naulaerts, Pedro J Ballester
Frontiers in Genetics
|
November 12, 2019
Paclitaxel Response Can Be Predicted With Interpretable Multi-Variate Classifiers Exploiting DNA-Methylation and miRNA Data
Alexandra Bomane, Anthony Gonçalves, Pedro J Ballester
Biomolecules
|
November 24, 2020
Identification and Validation of Carbonic Anhydrase II as the First Target of the Anti-Inflammatory Drug Actarit
Ghita Ghislat, Taufiq Rahman, Pedro J Ballester
Scientific Reports
|
April 26, 2017
Performance of machine-learning scoring functions in structure-based virtual screening
Maciej Wójcikowski, Pedro J Ballester, Pawel Siedlecki
BMC Medical Genomics
|
February 8, 2018
Unearthing new genomic markers of drug response by improved measurement of discriminative power
Cuong C Dang, Antonio Peón, Pedro J Ballester
Journal of Chemical Information and Modeling
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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 tumours
Stefan 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 data
Linh Nguyen, Cuong C Dang, Pedro J Ballester
Page
of 13
Search research articles
Search
Showing results (11-20 of 123) with videos related to
Sort By:
Page
of 13
Methods in Molecular Biology (Clifton, N.J.)
|
August 28, 2019
Building Machine-Learning Scoring Functions for Structure-Based Prediction of Intermolecular Binding Affinity
Maciej Wójcikowski, Pawel Siedlecki, Pedro J Ballester
Bioinformatics (Oxford, England)
|
March 19, 2010
A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking
Pedro J Ballester, John B O Mitchell
Scientific Reports
|
June 21, 2017
Predicting the Reliability of Drug-target Interaction Predictions with Maximum Coverage of Target Space
Antonio Peón, Stefan Naulaerts, Pedro J Ballester
Frontiers in Genetics
|
November 12, 2019
Paclitaxel Response Can Be Predicted With Interpretable Multi-Variate Classifiers Exploiting DNA-Methylation and miRNA Data
Alexandra Bomane, Anthony Gonçalves, Pedro J Ballester
Biomolecules
|
November 24, 2020
Identification and Validation of Carbonic Anhydrase II as the First Target of the Anti-Inflammatory Drug Actarit
Ghita Ghislat, Taufiq Rahman, Pedro J Ballester
Scientific Reports
|
April 26, 2017
Performance of machine-learning scoring functions in structure-based virtual screening
Maciej Wójcikowski, Pedro J Ballester, Pawel Siedlecki
BMC Medical Genomics
|
February 8, 2018
Unearthing new genomic markers of drug response by improved measurement of discriminative power
Cuong C Dang, Antonio Peón, Pedro J Ballester
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 tumours
Stefan 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 data
Linh Nguyen, Cuong C Dang, Pedro J Ballester
Page
of 13