Jeffrey Skolnick

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 11

Top Topics

High Throughput

Protein Structure

Subcellular Localization

Hierarchical Text Classification

Top Venues

J. Chem. Inf. Model.

J. Comput. Chem.

Publications

Vidit Jain, Mukund Rungta, Yuchen Zhuang, Yue Yu, Zeyu Wang, Mu Gao, Jeffrey Skolnick, Chao Zhang
HiGen: Hierarchy-Aware Sequence Generation for Hierarchical Text Classification. EACL (1) (2024)
Vidit Jain, Mukund Rungta, Yuchen Zhuang, Yue Yu, Zeyu Wang, Mu Gao, Jeffrey Skolnick, Chao Zhang
HiGen: Hierarchy-Aware Sequence Generation for Hierarchical Text Classification. CoRR (2024)
Russell B. Davidson, Mark Coletti, Mu Gao, Bryan Piatkowski, Avinash Sreedasyam, Farhan Quadir, David J. Weston, Jeremy Schmutz, Jianlin Cheng, Jeffrey Skolnick, Jerry M. Parks, Ada Sedova
and proteome-scale annotation. Bioinform. 39 (8) (2023)
Mu Gao, Peik Lund-Andersen, Alex Morehead, Sajid Mahmud, Chen Chen, Xiao Chen, Nabin Giri, Raj S. Roy, Farhan Quadir, T. Chad Effler, Ryan Prout, Subil Abraham, Wael R. Elwasif, Nicholas Quentin Haas, Jeffrey Skolnick, Jianlin Cheng, Ada Sedova
High-Performance Deep Learning Toolbox for Genome-Scale Prediction of Protein Structure and Function. MLHPC@SC (2021)
Hongyi Zhou, Hongnan Cao, Jeffrey Skolnick
FRAGSITE: A Fragment-Based Approach for Virtual Ligand Screening. J. Chem. Inf. Model. 61 (4) (2021)
Mu Gao, Jeffrey Skolnick
A General Framework to Learn Tertiary Structure for Protein Sequence Characterization. Frontiers Bioinform. 1 (2021)
Jeffrey Skolnick, Mu Gao, Hongyi Zhou, Suresh Singh
AlphaFold 2: Why It Works and Its Implications for Understanding the Relationships of Protein Sequence, Structure, and Function. J. Chem. Inf. Model. 61 (10) (2021)
Mu Gao, Jeffrey Skolnick
A novel sequence alignment algorithm based on deep learning of the protein folding code. Bioinform. 37 (4) (2021)
Hongyi Zhou, Hongnan Cao, Jeffrey Skolnick
FINDSITEcomb2.0: A New Approach for Virtual Ligand Screening of Proteins and Virtual Target Screening of Biomolecules. J. Chem. Inf. Model. 58 (11) (2018)
Sam Tonddast-Navaei, Bharath Srinivasan, Jeffrey Skolnick
On the importance of composite protein multiple ligand interactions in protein pockets. J. Comput. Chem. 38 (15) (2017)
Hongyi Zhou, Jeffrey Skolnick
A knowledge-based approach for predicting gene-disease associations. Bioinform. 32 (18) (2016)
Ambrish Roy, Bharath Srinivasan, Jeffrey Skolnick
: A Virtual Screening Pipeline Based on Template Pocket and Ligand Similarity. J. Chem. Inf. Model. 55 (8) (2015)
Hui Sun Lee, Sunhwan Jo, Srayanta Mukherjee, Sang-Jun Park, Jeffrey Skolnick, Jooyoung Lee, Wonpil Im
GS-align for glycan structure alignment and similarity measurement. Bioinform. 31 (16) (2015)
Ambrish Roy, Jeffrey Skolnick
LIGSIFT: an open-source tool for ligand structural alignment and virtual screening. Bioinform. 31 (4) (2015)
Bharath Srinivasan, Hongyi Zhou, Julia Kubanek, Jeffrey Skolnick
Experimental validation of FINDSITEcomb virtual ligand screening results for eight proteins yields novel nanomolar and micromolar binders. J. Cheminformatics 6 (1) (2014)
Tadashi Ando, Jeffrey Skolnick
Sliding of Proteins Non-specifically Bound to DNA: Brownian Dynamics Studies with Coarse-Grained Protein and DNA Models. PLoS Comput. Biol. 10 (12) (2014)
Mu Gao, Jeffrey Skolnick
A Comprehensive Survey of Small-Molecule Binding Pockets in Proteins. PLoS Comput. Biol. 9 (10) (2013)
Sunhwan Jo, Hui Sun Lee, Jeffrey Skolnick, Wonpil Im
Restricted N-glycan Conformational Space in the PDB and Its Implication in Glycan Structure Modeling. PLoS Comput. Biol. 9 (3) (2013)
Mu Gao, Jeffrey Skolnick
APoc: large-scale identification of similar protein pockets. Bioinform. 29 (5) (2013)
Hongyi Zhou, Jeffrey Skolnick
: A Threading/Structure-Based, Proteomic-Scale Virtual Ligand Screening Approach. J. Chem. Inf. Model. 53 (1) (2013)
Narendra Kumar, Jeffrey Skolnick
: application of a high-precision enzyme function predictor to 396 proteomes. Bioinform. 28 (20) (2012)
Wei Guan, Arkadas Ozakin, Alexander G. Gray, Jose Borreguero, Shashi Bhushan Pandit, Anna Jagielska, Liliana Wroblewska, Jeffrey Skolnick
Learning Protein Folding Energy Functions. ICDM (2011)
Michal Brylinski, Jeffrey Skolnick
: Low-resolution refinement for ligand comparative modeling. J. Comput. Chem. 31 (5) (2010)
Mu Gao, Jeffrey Skolnick
iAlign: a method for the structural comparison of protein-protein interfaces. Bioinform. 26 (18) (2010)
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) (2010)
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) (2010)
Jeffrey Skolnick, Michal Brylinski
FINDSITE: a combined evolution/structure-based approach to protein function prediction. Briefings Bioinform. 10 (4) (2009)
Michal Brylinski, Jeffrey Skolnick
: A Threading-Based Approach to Ligand Homology Modeling. PLoS Comput. Biol. 5 (6) (2009)
Adrian K. Arakaki, Ying Huang, Jeffrey Skolnick
: enzyme function inference by a combined approach enhanced by machine learning. BMC Bioinform. 10 (2009)
Mu Gao, Jeffrey Skolnick
From Nonspecific DNA-Protein Encounter Complexes to the Prediction of DNA-Protein Interactions. PLoS Comput. Biol. 5 (4) (2009)
Mu Gao, Jeffrey Skolnick
A Threading-Based Method for the Prediction of DNA-Binding Proteins with Application to the Human Genome. PLoS Comput. Biol. 5 (11) (2009)
Ryangguk Kim, Jeffrey Skolnick
Assessment of programs for ligand binding affinity prediction. J. Comput. Chem. 29 (8) (2008)
Michal Brylinski, Jeffrey Skolnick
Q-Dock: Low-resolution flexible ligand docking with pocket-specific threading restraints. J. Comput. Chem. 29 (10) (2008)
Shashi Bhushan Pandit, Jeffrey Skolnick
Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score. BMC Bioinform. 9 (2008)
Piotr Rotkiewicz, Jeffrey Skolnick
Fast procedure for reconstruction of full-atom protein models from reduced representations. J. Comput. Chem. 29 (9) (2008)
Liliana Wroblewska, Jeffrey Skolnick
Can a physics-based, all-atom potential find a protein's native structure among misfolded structures? I. Large scale AMBER benchmarking. J. Comput. Chem. 28 (12) (2007)
Anna Jagielska, Jeffrey Skolnick
-helix versus strand stability in homopolypeptides and its implications for the accuracy of the Amber force field. J. Comput. Chem. 28 (10) (2007)
Yang Zhang, Mark E. DeVries, Jeffrey Skolnick
Correction: Structure Modeling of All Identified G Protein-Coupled Receptors in the Human Genome. PLoS Comput. Biol. 2 (3) (2006)
Yang Zhang, Mark E. DeVries, Jeffrey Skolnick
Structure Modeling of All Identified G Protein-Coupled Receptors in the Human Genome. PLoS Comput. Biol. 2 (2) (2006)
Eckart Bindewald, Jeffrey Skolnick
A scoring function for docking ligands to low-resolution protein structures. J. Comput. Chem. 26 (4) (2005)
Adrian K. Arakaki, Yang Zhang, Jeffrey Skolnick
Large-scale assessment of the utility of low-resolution protein structures for biochemical function assignment. Bioinform. 20 (7) (2004)
Yang Zhang, Jeffrey Skolnick
SPICKER: A clustering approach to identify near-native protein folds. J. Comput. Chem. 25 (6) (2004)
Michal J. Boniecki, Piotr Rotkiewicz, Jeffrey Skolnick, Andrzej Kolinski
Protein fragment reconstruction using various modeling techniques. J. Comput. Aided Mol. Des. 17 (11) (2003)
Marek Wojciechowski, Jeffrey Skolnick
Docking of small ligands to low-resolution and theoretically predicted receptor structures. J. Comput. Chem. 23 (1) (2002)
Marcos R. Betancourt, Jeffrey Skolnick
Finding the needle in a haystack: educing native folds from ambiguous ab initio protein structure predictions. J. Comput. Chem. 22 (3) (2001)
Jeffrey Skolnick, Andrzej Kolinski
Computational studies of protein folding. Comput. Sci. Eng. 3 (5) (2001)
Jeffrey Skolnick, Andrzej Kolinski
Computational studies of protein folding. Comput. Sci. Eng. 3 (3) (2001)
Yury V. Bukhman, Jeffrey Skolnick
BioMolQuest: integrated database-based retrieval of protein structural and functional information. Bioinform. 17 (5) (2001)
Jeffrey Skolnick, Richard H. Lathrop
Protein Structure Prediction - Session Introduction. Pacific Symposium on Biocomputing (1999)
Boris A. Reva, Dmitrii S. Rykunov, Alexei V. Finkelstein, Jeffrey Skolnick
Optimization of Protein Structure on Lattices Using a Self-Consistent Field Approach. J. Comput. Biol. 5 (3) (1998)
Boris A. Reva, Alexei V. Finkelstein, Jeffrey Skolnick
A self-consistent field optimization approach to build energetically and geometrically correct lattice models of proteins. RECOMB (1998)
Mariusz Milik, Andrzej Kolinski, Jeffrey Skolnick
Algorithm for rapid reconstruction of protein backbone from alpha carbon coordinates. J. Comput. Chem. 18 (1) (1997)
Mariusz Milik, Jeffrey Skolnick
An Object-Oriented Environment for Artifical Evolution of Protein Sequences: The Example of Rational Design of Transmembrane Sequences. Evolutionary Programming (1995)
Adam Godzik, Jeffrey Skolnick
Flexible algorithm for direct multiple alignment of protein structures and sequences. Comput. Appl. Biosci. 10 (6) (1994)
Maciej Baginki, Lucjan Piela, Jeffrey Skolnick
The ethylene group as a peptide bond mimicking unit: A theoretical conformational analysis. J. Comput. Chem. 14 (4) (1993)
Adam Godzik, Andrzej Kolinski, Jeffrey Skolnick
Lattice representations of globular proteins: How good are they? J. Comput. Chem. 14 (10) (1993)
Adam Godzik, Andrzej Kolinski, Jeffrey Skolnick
De novo and inverse folding predictions of protein structure and dynamics. J. Comput. Aided Mol. Des. 7 (4) (1993)