Jeffrey Skolnick

Mu Gao, Jeffrey Skolnick: APoc: large-scale identification of similar protein pockets. Bioinformatics 29(5): 597-604 (2013)

Narendra Kumar, Jeffrey Skolnick: EFICAz^2.5: application of a high-precision enzyme function predictor to 396 proteomes. Bioinformatics 28(20): 2687-2688 (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: 1062-1067

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. Bioinformatics 26(5): 687-688 (2010)

Mu Gao, Jeffrey Skolnick: iAlign: a method for the structural comparison of protein-protein interfaces. Bioinformatics 26(18): 2259-2265 (2010)

Michal Brylinski, Jeffrey Skolnick: Q-Dock^LHM: Low-resolution refinement for ligand comparative modeling. Journal of Computational Chemistry 31(5): 1093-1105 (2010)

Jeffrey Skolnick, Michal Brylinski: FINDSITE: a combined evolution/structure-based approach to protein function prediction. Briefings in Bioinformatics 10(4): 378-391 (2009)

Adrian K. Arakaki, Ying Huang, Jeffrey Skolnick: EFICAz²: enzyme function inference by a combined approach enhanced by machine learning. BMC Bioinformatics 10 (2009)

Mu Gao, Jeffrey Skolnick: From Nonspecific DNA-Protein Encounter Complexes to the Prediction of DNA-Protein Interactions. PLoS Computational Biology 5(4) (2009)

Michal Brylinski, Jeffrey Skolnick: FINDSITE^LHM: A Threading-Based Approach to Ligand Homology Modeling. PLoS Computational Biology 5(6) (2009)

Mu Gao, Jeffrey Skolnick: A Threading-Based Method for the Prediction of DNA-Binding Proteins with Application to the Human Genome. PLoS Computational Biology 5(11) (2009)

Shashi Bhushan Pandit, Jeffrey Skolnick: Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score. BMC Bioinformatics 9 (2008)

Ryangguk Kim, Jeffrey Skolnick: Assessment of programs for ligand binding affinity prediction. Journal of Computational Chemistry 29(8): 1316-1331 (2008)

Piotr Rotkiewicz, Jeffrey Skolnick: Fast procedure for reconstruction of full-atom protein models from reduced representations. Journal of Computational Chemistry 29(9): 1460-1465 (2008)

Michal Brylinski, Jeffrey Skolnick: Q-Dock: Low-resolution flexible ligand docking with pocket-specific threading restraints. Journal of Computational Chemistry 29(10): 1574-1588 (2008)

Anna Jagielska, Jeffrey Skolnick: Origin of intrinsic 3₁₀-helix versus strand stability in homopolypeptides and its implications for the accuracy of the Amber force field. Journal of Computational Chemistry 28(10): 1648-1657 (2007)

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. Journal of Computational Chemistry 28(12): 2059-2066 (2007)

Yang Zhang, Mark E. DeVries, Jeffrey Skolnick: Structure Modeling of All Identified G Protein-Coupled Receptors in the Human Genome. PLoS Computational Biology 2(2) (2006)

Yang Zhang, Mark E. DeVries, Jeffrey Skolnick: Correction: Structure Modeling of All Identified G Protein-Coupled Receptors in the Human Genome. PLoS Computational Biology 2(3) (2006)

Eckart Bindewald, Jeffrey Skolnick: A scoring function for docking ligands to low-resolution protein structures. Journal of Computational Chemistry 26(4): 374-383 (2005)

Adrian K. Arakaki, Yang Zhang, Jeffrey Skolnick: Large-scale assessment of the utility of low-resolution protein structures for biochemical function assignment. Bioinformatics 20(7): 1087-1096 (2004)

Yang Zhang, Jeffrey Skolnick: SPICKER: A clustering approach to identify near-native protein folds. Journal of Computational Chemistry 25(6): 865-871 (2004)

Michal Boniecki, Piotr Rotkiewicz, Jeffrey Skolnick, Andrzej Kolinski: Protein fragment reconstruction using various modeling techniques. Journal of Computer-Aided Molecular Design 17(11): 725-738 (2003)

Marek Wojciechowski II, Jeffrey Skolnick: Docking of small ligands to low-resolution and theoretically predicted receptor structures. Journal of Computational Chemistry 23(1): 189-197 (2002)

Yury V. Bukhman, Jeffrey Skolnick: BioMolQuest: integrated database-based retrieval of protein structural and functional information. Bioinformatics 17(5): 468-478 (2001)

Marcos R. Betancourt, Jeffrey Skolnick: Finding the needle in a haystack: educing native folds from ambiguous ab initio protein structure predictions. Journal of Computational Chemistry 22(3): 339-353 (2001)

Jeffrey Skolnick, Richard H. Lathrop: Protein Structure Prediction - Session Introduction. Pacific Symposium on Biocomputing 1999: 480-481

Boris A. Reva, Dmitrii S. Rykunov, Alexei V. Finkelstein, Jeffrey Skolnick: Optimization of Protein Structure on Lattices Using a Self-Consistent Field Approach. Journal of Computational Biology 5(3): 531-538 (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: 214-220

Mariusz Milik, Andrzej Kolinski, Jeffrey Skolnick: Algorithm for rapid reconstruction of protein backbone from alpha carbon coordinates. Journal of Computational Chemistry 18(1): 80-85 (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: 603-613

Adam Godzik, Jeffrey Skolnick: Flexible algorithm for direct multiple alignment of protein structures and sequences. Computer Applications in the Biosciences 10(6): 587-596 (1994)

Adam Godzik, Andrzej Kolinski, Jeffrey Skolnick: De novo and inverse folding predictions of protein structure and dynamics. Journal of Computer-Aided Molecular Design 7(4): 397-438 (1993)