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Michal Brylinski
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2020 – today
- 2024
- [j32]Mengmeng Liu, Gopal Srivastava, J. Ramanujam, Michal Brylinski:
Insights from Augmented Data Integration and Strong Regularization in Drug Synergy Prediction with SynerGNet. Mach. Learn. Knowl. Extr. 6(3): 1782-1797 (2024) - 2022
- [c3]Supratik Mukhopadhyay, Michal Brylinski, Adam Bess, Frej Berglind, Chris Galliano, Patrick F. McGrew:
DeepDrug: Applying AI for the Advancement of Drug Discovery. COMSNETS 2022: 667-674 - 2021
- [j31]Guannan Liu, Manali Singha, Limeng Pu, Prasanga Neupane, Joseph Feinstein, Hsiao-Chun Wu, J. Ramanujam, Michal Brylinski:
GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data. J. Cheminformatics 13(1): 58 (2021) - 2020
- [j30]Wentao Shi, Jeffrey Mitchell Lemoine, Abd-El-Monsif A. Shawky, Manali Singha, Limeng Pu, Shuangyan Yang, J. Ramanujam, Michal Brylinski:
BionoiNet: ligand-binding site classification with off-the-shelf deep neural network. Bioinform. 36(10): 3077-3083 (2020)
2010 – 2019
- 2019
- [j29]Misagh Naderi, Jeffrey Mitchell Lemoine, Rajiv Gandhi Govindaraj, Omar Kana, Wei Pan Feinstein, Michal Brylinski:
Binding site matching in rational drug design: algorithms and applications. Briefings Bioinform. 20(6): 2167-2184 (2019) - [j28]Omar Kana, Michal Brylinski:
Elucidating the druggability of the human proteome with eFindSite. J. Comput. Aided Mol. Des. 33(5): 509-519 (2019) - [j27]Limeng Pu, Rajiv Gandhi Govindaraj, Jeffrey Mitchell Lemoine, Hsiao-Chun Wu, Michal Brylinski:
DeepDrug3D: Classification of ligand-binding pockets in proteins with a convolutional neural network. PLoS Comput. Biol. 15(2) (2019) - [c2]Eroma Abeysinghe, Michal Brylinski, Marcus Christie, Suresh Marru, Marlon E. Pierce:
LSU Computational System Biology Gateway for Education. PEARC 2019: 112:1-112:4 - 2018
- [j26]Rajiv Gandhi Govindaraj, Michal Brylinski:
Comparative assessment of strategies to identify similar ligand-binding pockets in proteins. BMC Bioinform. 19(1): 91:1-91:17 (2018) - [c1]Eroma Abeysinghe, Michal Brylinski, Marcus Christie, Suresh Marru, Marlon E. Pierce:
The CSBG - LSU Gateway: Web based Hosted Gateway for Computational System Biology Application Tools from Louisiana State University. PEARC 2018: 100:1-100:4 - 2017
- [j25]Surabhi Maheshwari, Michal Brylinski:
Across-proteome modeling of dimer structures for the bottom-up assembly of protein-protein interaction networks. BMC Bioinform. 18(1): 257:1-257:14 (2017) - [j24]Tairan Liu, Misagh Naderi, Chris Alvin, Supratik Mukhopadhyay, Michal Brylinski:
Break Down in Order To Build Up: Decomposing Small Molecules for Fragment-Based Drug Design with eMolFrag. J. Chem. Inf. Model. 57(4): 627-631 (2017) - 2016
- [j23]Chen Wang, Gang Hu, Kui Wang, Michal Brylinski, Lei Xie, Lukasz A. Kurgan:
PDID: database of molecular-level putative protein-drug interactions in the structural human proteome. Bioinform. 32(4): 579-586 (2016) - [j22]Yun Ding, Ye Fang, Juana Moreno, J. Ramanujam, Mark Jarrell, Michal Brylinski:
Assessing the similarity of ligand binding conformations with the Contact Mode Score. Comput. Biol. Chem. 64: 403-413 (2016) - [j21]Misagh Naderi, Chris Alvin, Yun Ding, Supratik Mukhopadhyay, Michal Brylinski:
A graph-based approach to construct target-focused libraries for virtual screening. J. Cheminformatics 8(1): 14:1-14:16 (2016) - 2015
- [j20]Michal Brylinski:
Is the growth rate of Protein Data Bank sufficient to solve the protein structure prediction problem using template-based modeling? Bio Algorithms Med Syst. 11(1): 1-7 (2015) - [j19]Surabhi Maheshwari, Michal Brylinski:
Predicting protein interface residues using easily accessible on-line resources. Briefings Bioinform. 16(6): 1025-1034 (2015) - [j18]Yun Ding, Ye Fang, Wei Pan Feinstein, Jagannathan Ramanujam, David M. Koppelman, Juana Moreno, Michal Brylinski, Mark Jarrell:
GeauxDock: A novel approach for mixed-resolution ligand docking using a descriptor-based force field. J. Comput. Chem. 36(27): 2013-2026 (2015) - [j17]Wei Pan Feinstein, Michal Brylinski:
Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets. J. Cheminformatics 7: 18:1-18:10 (2015) - 2014
- [j16]Michal Brylinski:
eMatchSite: Sequence Order-Independent Structure Alignments of Ligand Binding Pockets in Protein Models. PLoS Comput. Biol. 10(9) (2014) - 2013
- [j15]Michal Brylinski, Wei Pan Feinstein:
eFindSite: Improved prediction of ligand binding sites in protein models using meta-threading, machine learning and auxiliary ligands. J. Comput. Aided Mol. Des. 27(6): 551-567 (2013) - [j14]Michal Brylinski:
Nonlinear Scoring Functions for Similarity-Based Ligand Docking and Binding Affinity Prediction. J. Chem. Inf. Model. 53(11): 3097-3112 (2013) - 2010
- [j13]Shashi Bhushan Pandit, Michal Brylinski, Hongyi Zhou, Mu Gao, Adrian K. Arakaki, Jeffrey Skolnick:
PSiFR: an integrated resource for prediction of protein structure and function. Bioinform. 26(5): 687-688 (2010) - [j12]Michal Brylinski, Jeffrey Skolnick:
Q-DockLHM: Low-resolution refinement for ligand comparative modeling. J. Comput. Chem. 31(5): 1093-1105 (2010) - [j11]Michal Brylinski, Jeffrey Skolnick:
Comprehensive Structural and Functional Characterization of the Human Kinome by Protein Structure Modeling and Ligand Virtual Screening. J. Chem. Inf. Model. 50(10): 1839-1854 (2010)
2000 – 2009
- 2009
- [j10]Jeffrey Skolnick, Michal Brylinski:
FINDSITE: a combined evolution/structure-based approach to protein function prediction. Briefings Bioinform. 10(4): 378-391 (2009) - [j9]Michal Brylinski, Jeffrey Skolnick:
FINDSITELHM: A Threading-Based Approach to Ligand Homology Modeling. PLoS Comput. Biol. 5(6) (2009) - 2008
- [j8]Michal Brylinski, Jeffrey Skolnick:
Q-Dock: Low-resolution flexible ligand docking with pocket-specific threading restraints. J. Comput. Chem. 29(10): 1574-1588 (2008) - 2007
- [j7]Michal Brylinski, Leszek Konieczny, Irena Roterman:
Is the protein folding an aim-oriented process? Human haemoglobin as example. Int. J. Bioinform. Res. Appl. 3(2): 234-260 (2007) - [j6]Michal Brylinski, Katarzyna Prymula, Wiktor Jurkowski, Marek Kochanczyk, Ewa Stawowczyk, Leszek Konieczny, Irena Roterman:
Prediction of Functional Sites Based on the Fuzzy Oil Drop Model. PLoS Comput. Biol. 3(5) (2007) - 2006
- [j5]Michal Brylinski, Leszek Konieczny, Irena Roterman:
Hydrophobic collapse in (in silico) protein folding. Comput. Biol. Chem. 30(4): 255-267 (2006) - [j4]Leszek Konieczny, Michal Brylinski, Irena Roterman:
Gauss-Function-Based Model of Hydrophobicity Density in Proteins. Silico Biol. 6(1-2): 15-22 (2006) - [j3]Michal Brylinski, Marek Kochanczyk, Leszek Konieczny, Irena Roterman:
Sequence-Structure-Function Relation Characterized in silico. Silico Biol. 6(6): 589-600 (2006) - 2004
- [j2]Michal Brylinski, Wiktor Jurkowski, Leszek Konieczny, Irena Roterman:
Limited conformational space for early-stage protein folding simulation. Bioinform. 20(2): 199-205 (2004) - [j1]Michal Brylinski, Leszek Konieczny, Irena Roterman:
SPI - Structure predictability index for protein sequences. Silico Biol. 5(3): 227-237 (2004)
Coauthor Index
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