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Michael K. Gilson
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2020 – today
- 2024
- [j48]Peter Eckmann
, Jake Anderson
Ligand-Based Compound Activity Prediction via Few-Shot Learning. J. Chem. Inf. Model. 64(14): 5492-5499 (2024) - [i5]Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K. Gilson, Rose Yu:
MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling. CoRR abs/2402.10387 (2024) - [i4]Vineet Thumuluri, Peter Eckmann, Michael K. Gilson, Rose Yu:
Technical report: Improving the properties of molecules generated by LIMO. CoRR abs/2407.14968 (2024) - [i3]Peter Eckmann, Dongxia Wu, Germano Heinzelmann, Michael K. Gilson, Rose Yu:
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning. CoRR abs/2410.11226 (2024) - 2023
- [i2]Peter Eckmann, Jake Anderson
Target-Free Compound Activity Prediction via Few-Shot Learning. CoRR abs/2311.16328 (2023) - 2022
- [c1]Peter Eckmann, Kunyang Sun, Bo Zhao
LIMO: Latent Inceptionism for Targeted Molecule Generation. ICML 2022: 5777-5792 - [i1]Peter Eckmann, Kunyang Sun, Bo Zhao, Mudong Feng, Michael K. Gilson, Rose Yu:
LIMO: Latent Inceptionism for Targeted Molecule Generation. CoRR abs/2206.09010 (2022) - 2021
- [j47]K. Kellett, David R. Slochower, Michael Schauperl, B. M. Duggan, Michael K. Gilson
Experimental characterization of the association of β-cyclodextrin and eight novel cyclodextrin derivatives with two guest compounds. J. Comput. Aided Mol. Des. 35(1): 95-104 (2021) - [j46]Teresa Danielle Bergazin
Enhancing water sampling of buried binding sites using nonequilibrium candidate Monte Carlo. J. Comput. Aided Mol. Des. 35(2): 167-177 (2021) - [j45]Sergio Alejandro Pinacho-Castellanos
Alignment-Free Antimicrobial Peptide Predictors: Improving Performance by a Thorough Analysis of the Largest Available Data Set. J. Chem. Inf. Model. 61(6): 3141-3157 (2021) - [j44]Sergio Alejandro Pinacho-Castellanos
Correction to Alignment-Free Antimicrobial Peptide Predictors: Improving Performance by a Thorough Analysis of the Largest Available Data Set. J. Chem. Inf. Model. 61(7): 3736 (2021) - [j43]Joel Ricci-Lopez
Improving Structure-Based Virtual Screening with Ensemble Docking and Machine Learning. J. Chem. Inf. Model. 61(11): 5362-5376 (2021) - 2020
- [j42]Michael K. Gilson, Rommie E. Amaro
Drug Design Data Resource, Grand Challenge 4, second of two issues. J. Comput. Aided Mol. Des. 34(2): 97 (2020) - [j41]Conor D. Parks, Zied Gaieb, Michael Chiu, Huanwang Yang, Chenghua Shao
D3R grand challenge 4: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies. J. Comput. Aided Mol. Des. 34(2): 99-119 (2020) - [j40]Andrea Rizzi
The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations. J. Comput. Aided Mol. Des. 34(5): 601-633 (2020)
2010 – 2019
- 2019
- [j39]Zied Gaieb, Conor D. Parks, Michael Chiu
D3R Grand Challenge 3: blind prediction of protein-ligand poses and affinity rankings. J. Comput. Aided Mol. Des. 33(1): 1-18 (2019) - [j38]Michael K. Gilson:
This issue: Drug Design Data Resource Grand Challenge 4, first of two issues. J. Comput. Aided Mol. Des. 33(12): 1009 (2019) - 2018
- [j37]Zied Gaieb, Shuai Liu, Symon Gathiaka, Michael Chiu
D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies. J. Comput. Aided Mol. Des. 32(1): 1-20 (2018) - [j36]Andrea Rizzi
Overview of the SAMPL6 host-guest binding affinity prediction challenge. J. Comput. Aided Mol. Des. 32(10): 937-963 (2018) - 2017
- [j35]Jian Yin, Niel M. Henriksen, David R. Slochower, Michael R. Shirts, Michael Chiu
Overview adcm43.bhtof the SAMPL5 host-guest challenge: Are we doing better? J. Comput. Aided Mol. Des. 31(1): 1-19 (2017) - [j34]Jian Yin, Niel M. Henriksen, David R. Slochower, Michael K. Gilson:
The SAMPL5 host-guest challenge: computing binding free energies and enthalpies from explicit solvent simulations by the attach-pull-release (APR) method. J. Comput. Aided Mol. Des. 31(1): 133-145 (2017) - [j33]Michael R. Shirts
Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset. J. Comput. Aided Mol. Des. 31(1): 147-161 (2017) - [j32]Michael R. Shirts
Erratum to: Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset. J. Comput. Aided Mol. Des. 31(8): 777 (2017) - 2016
- [j31]Symon Gathiaka, Shuai Liu, Michael Chiu
D3R grand challenge 2015: Evaluation of protein-ligand pose and affinity predictions. J. Comput. Aided Mol. Des. 30(9): 651-668 (2016) - [j30]Caitlin C. Bannan
Blind prediction of cyclohexane-water distribution coefficients from the SAMPL5 challenge. J. Comput. Aided Mol. Des. 30(11): 927-944 (2016) - [j29]Steven Ramsey, Crystal Nguyen, Romelia Salomón-Ferrer, Ross C. Walker, Michael K. Gilson, Tom Kurtzman:
Solvation thermodynamic mapping of molecular surfaces in AmberTools: GIST. J. Comput. Chem. 37(21): 2029-2037 (2016) - [j28]Michael K. Gilson
BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology. Nucleic Acids Res. 44(Database-Issue): 1045-1053 (2016) - 2015
- [j27]George Nicola, Michael R. Berthold, Michael P. Hedrick, Michael K. Gilson:
Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME. Database J. Biol. Databases Curation 2015 (2015) - 2014
- [j26]Hari S. Muddana, Neil V. Sapra, Andrew T. Fenley, Michael K. Gilson:
The SAMPL4 hydration challenge: evaluation of partial charge sets with explicit-water molecular dynamics simulations. J. Comput. Aided Mol. Des. 28(3): 277-287 (2014) - [j25]Hari S. Muddana, Andrew T. Fenley, David L. Mobley
The SAMPL4 host-guest blind prediction challenge: an overview. J. Comput. Aided Mol. Des. 28(4): 305-317 (2014) - [j24]Hari S. Muddana, Jian Yin, Neil V. Sapra, Andrew T. Fenley, Michael K. Gilson:
Blind prediction of SAMPL4 cucurbit[7]uril binding affinities with the mining minima method. J. Comput. Aided Mol. Des. 28(4): 463-474 (2014) - 2013
- [j23]Camilo Velez-Vega, Michael K. Gilson:
Overcoming dissipation in the calculation of standard binding free energies by ligand extraction. J. Comput. Chem. 34(27): 2360-2371 (2013) - 2012
- [j22]Hari S. Muddana, C. Daniel Varnado, Christopher W. Bielawski, Adam R. Urbach, Lyle Isaacs
Blind prediction of host-guest binding affinities: a new SAMPL3 challenge. J. Comput. Aided Mol. Des. 26(5): 475-487 (2012) - [j21]Hari S. Muddana, Michael K. Gilson:
Prediction of SAMPL3 host-guest binding affinities: evaluating the accuracy of generalized force-fields. J. Comput. Aided Mol. Des. 26(5): 517-525 (2012) - [j20]Nikolai Hecker
SuperTarget goes quantitative: update on drug-target interactions. Nucleic Acids Res. 40(Database-Issue): 1113-1117 (2012) - 2010
- [j19]Vladimir Hnizdo, Michael K. Gilson:
Thermodynamic and Differential Entropy under a Change of Variables. Entropy 12(3): 578-590 (2010)
2000 – 2009
- 2008
- [j18]Vladimir Hnizdo, Jun Tan, Benjamin J. Killian, Michael K. Gilson:
Efficient calculation of configurational entropy from molecular simulations by combining the mutual-information expansion and nearest-neighbor methods. J. Comput. Chem. 29(10): 1605-1614 (2008) - 2007
- [j17]Wei Chen, Michael K. Gilson:
ConCept: de Novo Design of Synthetic Receptors for Targeted Ligands. J. Chem. Inf. Model. 47(2): 425-434 (2007) - [j16]Wei Chen, Michael K. Gilson:
ConCept: de Novo Design of Synthetic Receptors for Targeted Ligands [J. Chem. Inf. Model, 47, 425-434 (2007)]. J. Chem. Inf. Model. 47(5): 1998 (2007) - [j15]Tiqing Liu, Yuhmei Lin, Xin Wen, Robert N. Jorissen
BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res. 35(Database-Issue): 198-201 (2007) - 2006
- [j14]Visvaldas Kairys
Screening Drug-Like Compounds by Docking to Homology Models: A Systematic Study. J. Chem. Inf. Model. 46(1): 365-379 (2006) - 2005
- [j13]Robert N. Jorissen
Virtual Screening of Molecular Databases Using a Support Vector Machine. J. Chem. Inf. Model. 45(3): 549-561 (2005) - 2004
- [j12]Wei Chen, Jing Huang, Michael K. Gilson:
Identification of Symmetries in Molecules and Complexes. J. Chem. Inf. Model. 44(4): 1301-1313 (2004) - [j11]Miguel X. Fernandes
Comparing Ligand Interactions with Multiple Receptors via Serial Docking. J. Chem. Inf. Model. 44(6): 1961-1970 (2004) - 2003
- [j10]Chia-En Chang, Michael K. Gilson:
Tork: Conformational analysis method for molecules and complexes. J. Comput. Chem. 24(16): 1987-1998 (2003) - [j9]Michael K. Gilson, Hillary S. R. Gilson, Michael J. Potter:
Fast Assignment of Accurate Partial Atomic Charges: An Electronegativity Equalization Method that Accounts for Alternate Resonance Forms. J. Chem. Inf. Comput. Sci. 43(6): 1982-1997 (2003) - [j8]Jeremy D. Glasner, Paul Liss, Guy Plunkett III, Aaron E. Darling
ASAP, a systematic annotation package for community analysis of genomes. Nucleic Acids Res. 31(1): 147-151 (2003) - 2002
- [j7]Xi Chen, Yuhmei Lin, Ming Liu, Michael K. Gilson:
The Binding Database: data management and interface design. Bioinform. 18(1): 130-139 (2002) - [j6]Ray Luo
Accelerated Poisson-Boltzmann calculations for static and dynamic systems. J. Comput. Chem. 23(13): 1244-1253 (2002) - [j5]Visvaldas Kairys
Enhanced docking with the mining minima optimizer: Acceleration and side-chain flexibility. J. Comput. Chem. 23(16): 1656-1670 (2002) - 2001
- [j4]Laurent David, Ray Luo
Ligand-receptor docking with the Mining Minima optimizer. J. Comput. Aided Mol. Des. 15(2): 157-171 (2001) - 2000
- [j3]Laurent David, Ray Luo, Michael K. Gilson:
Comparison of generalized born and poisson models: Energetics and dynamics of HIV protease. J. Comput. Chem. 21(4): 295-309 (2000)
1990 – 1999
- 1996
- [j2]Jan Antosiewicz, James M. Briggs, Adrian H. Elcock
Computing ionization states of proteins with a detailed charge model. J. Comput. Chem. 17(14): 1633-1644 (1996) - 1991
- [j1]Michael K. Gilson, Barry Honig
The inclusion of electrostatic hydration energies in molecular mechanics calculations. J. Comput. Aided Mol. Des. 5(1): 5-20 (1991)
Coauthor Index
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last updated on 2024-11-25 22:45 CET by the dblp team
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