Pedro Ballester
机构: Royal Society Wolfson Fellow & Senior Lecturer at Imperial College London
主页: imperial.ac.uk
每年引用次数
引用次数
引用: 6,239
H-指数: 38
I10-指数 : 64
出版物: 99
Our calibrated model has poor predictive value: An example from the petroleum industry
J.N. Carter , P.J. Ballester , Z. Tavassoli , P.R. King
Reliability Engineering & System Safety 91 ( 10) 1373 -1381
38
2006
Real-parameter optimization performance study on the CEC-2005 benchmark with SPC-PNX
P.J. Ballester , J. Stephenson , J.N. Carter , K. Gallagher
congress on evolutionary computation 1 498 -505
91
2005
A Multiparent Version of the Parent-Centric Normal Crossover for Multimodal Optimization
P.J. Ballester , W.G. Richards
ieee international conference on evolutionary computation 2999 -3006
3
2006
A Real Parameter Genetic Algorithm for Cluster Identification in History Matching
J.N. Carter , P.J. Ballester
ECMOR IX - 9th European Conference on the Mathematics of Oil Recovery
10
2004
A stochastic spiking neural network for virtual screening
A. Morro , V. Canals , A. Oliver , M.L. Alomar
IEEE transactions on neural networks and learning systems 29 ( 4) 1371 -1375
59
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
F1000Research 5 2927
15
2016
Biochemical evaluation of virtual screening methods reveals a cell-active inhibitor of the cancer-promoting phosphatases of regenerating liver.
Birgit Hoeger , Maren Diether , Pedro J. Ballester , Maja Köhn
European Journal of Medicinal Chemistry 88 89 -100
39
2014
Paclitaxel Response Can Be Predicted With Interpretable Multi-Variate Classifiers Exploiting DNA-Methylation and miRNA Data.
Alexandra Bomane , Anthony Gonçalves , Pedro J. Ballester
Frontiers in Genetics 10 1041
9
2019
Characterising the parameter space of a highly nonlinear inverse problem
Pedro J. Ballester , Jonathan N. Carter
Inverse Problems in Science and Engineering 14 ( 2) 171 -191
13
2006
Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets.
Hongjian Li , Kwong-Sak Leung , Man-Hon Wong , Pedro J. Ballester
Molecular Informatics 34 115 -126
96
2015
Prospective virtual screening with Ultrafast Shape Recognition: the identification of novel inhibitors of arylamine N-acetyltransferases
Pedro J. Ballester , Isaac Westwood , Nicola Laurieri , Edith Sim
Journal of the Royal Society Interface 7 ( 43) 335 -342
59
2010
Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification
Pedro J. Ballester , Martina Mangold , Nigel I. Howard , Richard L. Marchese Robinson
Journal of the Royal Society Interface 9 ( 77) 3196 -3207
51
2012
Drug Repurposing for Covid-19: Discovery of Potential Small-Molecule Inhibitors of Spike Protein-ACE2 Receptor Interaction Through Virtual Screening and Consensus Scoring
Sachin Patil , Jeremy Hofer , Pedro J. Ballester , Elena Fattakhova
ChemRxiv
8
2020
Machine learning scoring functions based on random forest and support vector regression
Pedro J. Ballester
pattern recognition in bioinformatics 14 -25
13
2012
Comments on “Leave-Cluster-Out Cross-Validation Is Appropriate for Scoring Functions Derived from Diverse Protein Data Sets”: Significance for the Validation of Scoring Functions
Pedro J. Ballester , John B. O. Mitchell
Journal of Chemical Information and Modeling 51 ( 8) 1739 -1741
31
2011
Cancer Cell Line Profiler (CCLP): a webserver for the prediction of compound activity across the NCI60 panel
Isidro Cortés-Ciriano , Daniel S. Murrell , Bernard Chetrit , Andreas Bender
bioRxiv 105478
2
2017
Ultrafast shape recognition to search compound databases for similar molecular shapes.
Pedro J. Ballester , W. Graham Richards
Journal of Computational Chemistry 28 ( 10) 1711 -1723
228
2007
Unearthing new genomic markers of drug response by improved measurement of discriminative power
Cuong C. Dang , Antonio Peón , Pedro J. Ballester
BMC Medical Genomics 11 ( 1) 1 -14
2
2018
Precision and recall oncology: combining multiple gene mutations for improved identification of drug-sensitive tumours
Stefan Naulaerts , Cuong C. Dang , Pedro J. Ballester
Oncotarget 8 ( 57) 97025 -97040
18
2017
A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking
Pedro J. Ballester , John B. O. Mitchell
Bioinformatics 26 ( 9) 1169 -1175
660
2010