Michal Brylinski

36 papers Misc 1Journal 33Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	EC2Vec: A Machine Learning Method to Embed Enzyme Commission (EC) Numbers into Vector Representations. J. Chem. Inf. Model. Mengmeng Liu, Xialong Ni, J. Ramanujam, Michal Brylinski
2025	J	`jnl`	Harnessing Large-Scale University Registrar Data for Predictive Insights: A Data-Driven Approach to Forecasting Undergraduate Student Success with Convolutional Autoencoders. Mach. Learn. Knowl. Extr. Mohammad Erfan Shoorangiz, Michal Brylinski
2024	J	`jnl`	Insights from Augmented Data Integration and Strong Regularization in Drug Synergy Prediction with SynerGNet. Mach. Learn. Knowl. Extr. Mengmeng Liu, Gopal N. Srivastava, J. Ramanujam, Michal Brylinski
2022	Misc	`conf`	DeepDrug: Applying AI for the Advancement of Drug Discovery. COMSNETS Supratik Mukhopadhyay, Michal Brylinski, Adam Bess, Frej Berglind, Chris Galliano, Patrick F. McGrew
2021	J	`jnl`	GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data. J. Cheminformatics Guannan Liu, Manali Singha, Limeng Pu, Prasanga Neupane, Joseph Feinstein, Hsiao-Chun Wu, J. Ramanujam, Michal Brylinski
2020	J	`jnl`	BionoiNet: ligand-binding site classification with off-the-shelf deep neural network. Bioinform. Wentao Shi, Jeffrey Mitchell Lemoine, Abd-El-Monsif A. Shawky, Manali Singha, Limeng Pu, Shuangyan Yang, J. Ramanujam, Michal Brylinski
2019	J	`jnl`	Binding site matching in rational drug design: algorithms and applications. Briefings Bioinform. Misagh Naderi, Jeffrey Mitchell Lemoine, Rajiv Gandhi Govindaraj, Omar Kana, Wei Pan Feinstein, Michal Brylinski
2019	J	`jnl`	DeepDrug3D: Classification of ligand-binding pockets in proteins with a convolutional neural network. PLoS Comput. Biol. Limeng Pu, Rajiv Gandhi Govindaraj, Jeffrey Mitchell Lemoine, Hsiao-Chun Wu, Michal Brylinski
2019	J	`jnl`	Elucidating the druggability of the human proteome with eFindSite. J. Comput. Aided Mol. Des. Omar Kana, Michal Brylinski
2019	—	`conf`	LSU Computational System Biology Gateway for Education. PEARC Eroma Abeysinghe, Michal Brylinski, Marcus Christie, Suresh Marru, Marlon E. Pierce
2018	J	`jnl`	Comparative assessment of strategies to identify similar ligand-binding pockets in proteins. BMC Bioinform. Rajiv Gandhi Govindaraj, Michal Brylinski
2018	—	`conf`	The CSBG - LSU Gateway: Web based Hosted Gateway for Computational System Biology Application Tools from Louisiana State University. PEARC Eroma Abeysinghe, Michal Brylinski, Marcus Christie, Suresh Marru, Marlon E. Pierce
2017	J	`jnl`	Across-proteome modeling of dimer structures for the bottom-up assembly of protein-protein interaction networks. BMC Bioinform. Surabhi Maheshwari, Michal Brylinski
2017	J	`jnl`	Break Down in Order To Build Up: Decomposing Small Molecules for Fragment-Based Drug Design with J. Chem. Inf. Model. Tairan Liu, Misagh Naderi, Chris Alvin, Supratik Mukhopadhyay, Michal Brylinski
2016	J	`jnl`	A graph-based approach to construct target-focused libraries for virtual screening. J. Cheminformatics Misagh Naderi, Chris Alvin, Yun Ding, Supratik Mukhopadhyay, Michal Brylinski
2016	J	`jnl`	Assessing the similarity of ligand binding conformations with the Contact Mode Score. Comput. Biol. Chem. Yun Ding, Ye Fang, Juana Moreno, J. Ramanujam, Mark Jarrell, Michal Brylinski
2016	J	`jnl`	PDID: database of molecular-level putative protein-drug interactions in the structural human proteome. Bioinform. Chen Wang, Gang Hu, Kui Wang, Michal Brylinski, Lei Xie, Lukasz A. Kurgan
2015	J	`jnl`	Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets. J. Cheminformatics Wei Pan Feinstein, Michal Brylinski
2015	J	`jnl`	GeauxDock: A novel approach for mixed-resolution ligand docking using a descriptor-based force field. J. Comput. Chem. Yun Ding, Ye Fang, Wei Pan Feinstein, Jagannathan Ramanujam, David M. Koppelman, Juana Moreno, Michal Brylinski, Mark Jarrell
2015	J	`jnl`	Is the growth rate of Protein Data Bank sufficient to solve the protein structure prediction problem using template-based modeling? Bio Algorithms Med Syst. Michal Brylinski
2015	J	`jnl`	Predicting protein interface residues using easily accessible on-line resources. Briefings Bioinform. Surabhi Maheshwari, Michal Brylinski
2013	J	`jnl`	Nonlinear Scoring Functions for Similarity-Based Ligand Docking and Binding Affinity Prediction. J. Chem. Inf. Model. Michal Brylinski
2013	J	`jnl`	eFindSite: Improved prediction of ligand binding sites in protein models using meta-threading, machine learning and auxiliary ligands. J. Comput. Aided Mol. Des. Michal Brylinski, Wei Pan Feinstein
2010	J	`jnl`	Comprehensive Structural and Functional Characterization of the Human Kinome by Protein Structure Modeling and Ligand Virtual Screening. J. Chem. Inf. Model. Michal Brylinski, Jeffrey Skolnick
2010	J	`jnl`	PSiFR: an integrated resource for prediction of protein structure and function. Bioinform. Shashi Bhushan Pandit, Michal Brylinski, Hongyi Zhou, Mu Gao, Adrian K. Arakaki, Jeffrey Skolnick
2010	J	`jnl`	Q-Dock J. Comput. Chem. Michal Brylinski, Jeffrey Skolnick
2009	J	`jnl`	FINDSITE PLoS Comput. Biol. Michal Brylinski, Jeffrey Skolnick
2009	J	`jnl`	FINDSITE: a combined evolution/structure-based approach to protein function prediction. Briefings Bioinform. Jeffrey Skolnick, Michal Brylinski
2008	J	`jnl`	Q-Dock: Low-resolution flexible ligand docking with pocket-specific threading restraints. J. Comput. Chem. Michal Brylinski, Jeffrey Skolnick
2007	J	`jnl`	Is the protein folding an aim-oriented process? Human haemoglobin as example. Int. J. Bioinform. Res. Appl. Michal Brylinski, Leszek Konieczny, Irena Roterman
2007	J	`jnl`	Prediction of Functional Sites Based on the Fuzzy Oil Drop Model. PLoS Comput. Biol. Michal Brylinski, Katarzyna Prymula, Wiktor Jurkowski, Marek Kochanczyk, Ewa Stawowczyk, Leszek Konieczny, Irena Roterman
2006	J	`jnl`	Gauss-Function-Based Model of Hydrophobicity Density in Proteins. Silico Biol. Leszek Konieczny, Michal Brylinski, Irena Roterman
2006	J	`jnl`	Hydrophobic collapse in ( Comput. Biol. Chem. Michal Brylinski, Leszek Konieczny, Irena Roterman
2006	J	`jnl`	Sequence-Structure-Function Relation Characterized in silico. Silico Biol. Michal Brylinski, Marek Kochanczyk, Leszek Konieczny, Irena Roterman
2004	J	`jnl`	Limited conformational space for early-stage protein folding simulation. Bioinform. Michal Brylinski, Wiktor Jurkowski, Leszek Konieczny, Irena Roterman
2004	J	`jnl`	SPI - Structure predictability index for protein sequences. Silico Biol. Michal Brylinski, Leszek Konieczny, Irena Roterman