Alexios Koutsoukas
Alexios Koutsoukas
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From in silico target prediction to multi-target drug design: Current databases, methods and applications
A Koutsoukas, B Simms, J Kirchmair, PJ Bond, AV Whitmore, S Zimmer, ...
Journal of proteomics 74 (12), 2554-2574, 2011
Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data
A Koutsoukas, KJ Monaghan, X Li, J Huan
Journal of cheminformatics 9 (1), 1-13, 2017
In silico target predictions: defining a benchmarking data set and comparison of performance of the multiclass Naïve Bayes and Parzen-Rosenblatt window
A Koutsoukas, R Lowe, Y KalantarMotamedi, HY Mussa, W Klaffke, ...
Journal of chemical information and modeling 53 (8), 1957-1966, 2013
How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space
A Koutsoukas, S Paricharak, WRJD Galloway, DR Spring, AP IJzerman, ...
Journal of chemical information and modeling 54 (1), 230-242, 2014
Chemogenomics approaches to rationalizing the mode-of-action of traditional Chinese and Ayurvedic medicines
F Mohd Fauzi, A Koutsoukas, R Lowe, K Joshi, TP Fan, RC Glen, ...
Journal of Chemical Information and Modeling 53 (3), 661-673, 2013
Anti-cancer drug development: computational strategies to identify and target proteins involved in cancer metabolism
L Mak, S Liggi, L Tan, K Kusonmano, J M Rollinger, A Koutsoukas, ...
Current pharmaceutical design 19 (4), 532-577, 2013
AP-Net: An atomic-pairwise neural network for smooth and transferable interaction potentials
CDS Zachary L. Glick, Derek P. Metcalf, Alexios Koutsoukas, Steven A. Spronk ...
The Journal of Chemical Physics 153 (4), 2020
Extending in silico mechanism-of-action analysis by annotating targets with pathways: application to cellular cytotoxicity readouts
S Liggi, G Drakakis, A Koutsoukas, I Cortes–Ciriano, P Martínez–Alonso, ...
Future Medicinal Chemistry 6 (18), 2029-2056, 2014
Predictive toxicology: modeling chemical induced toxicological response combining circular fingerprints with random forest and support vector machine
A Koutsoukas, J St. Amand, M Mishra, J Huan
Frontiers in Environmental Science 4, 11, 2016
Diversity Selection of Compounds Based on ‘Protein Affinity Fingerprints’ Improves Sampling of Bioactive Chemical Space
HP Nguyen, A Koutsoukas, F Mohd Fauzi, G Drakakis, M Maciejewski, ...
Chemical Biology & Drug Design 82 (3), 252-266, 2013
Approaches for machine learning intermolecular interaction energies and application to energy components from symmetry adapted perturbation theory
DP Metcalf, A Koutsoukas, SA Spronk, BL Claus, DA Loughney, ...
The Journal of Chemical Physics 152 (7), 074103, 2020
Improving the prediction of organism-level toxicity through integration of chemical, protein target and cytotoxicity qHTS data
CHG Allen, A Koutsoukas, I Cortés-Ciriano, DS Murrell, TE Malliavin, ...
Toxicology research 5 (3), 883-894, 2016
Linking Ayurveda and Western medicine by integrative analysis
FM Fauzi, A Koutsoukas, R Lowe, K Joshi, TP Fan, RC Glen, A Bender
Journal of Ayurveda and integrative medicine 4 (2), 117, 2013
Comparing global and local likelihood score thresholds in multiclass laplacian-modified naive bayes protein target prediction
G Drakakis, A Koutsoukas, S C Brewerton, M J Bodkin, D A Evans, ...
Combinatorial Chemistry & High Throughput Screening 18 (3), 323-330, 2015
Experimental validation of in silico target predictions on synergistic protein targets
I Cortes-Ciriano, A Koutsoukas, O Abian, RC Glen, A Velazquez-Campoy, ...
MedChemComm 4 (1), 278-288, 2013
Cartesian message passing neural networks for directional properties: Fast and transferable atomic multipoles
ZL Glick, A Koutsoukas, DL Cheney, CD Sherrill
The Journal of Chemical Physics 154 (22), 224103, 2021
CLIFF: A component-based, machine-learned, intermolecular force field
JB Schriber, DR Nascimento, A Koutsoukas, SA Spronk, DL Cheney, ...
The Journal of Chemical Physics 154 (18), 184110, 2021
Investigating multiview and multitask learning frameworks for predicting drug-disease associations
SN Chandrasekaran, A Koutsoukas, J Huan
Proceedings of the 7th ACM International Conference on Bioinformatics …, 2016
In-Silico Extraction of Design Ideas Using MMPA-by-QSAR and its Application on ADME Endpoints
A Koutsoukas, G Chang, CE Keefer
Journal of Chemical Information and Modeling 59 (1), 477-485, 2018
Using machine learning techniques for rationalising phenotypic readouts from a rat sleeping model
G Drakakis, A Koutsoukas, SC Brewerton, DDE Evans, A Bender
Journal of Cheminformatics 5 (1), 1-1, 2013
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