• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 34 matches

• 2024
• 
  Francesc Sabanés Zariquiey, Raimondas Galvelis, Emilio Gallicchio, John D. Chodera, Thomas E. Markland, Gianni De Fabritiis:
  Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials. J. Chem. Inf. Model. 64(5): 1481-1485 (2024)
• 
  Peter K. Eastman, Benjamin P. Pritchard, John D. Chodera, Thomas E. Markland:
  Nutmeg and SPICE: Models and Data for Biomolecular Machine Learning. CoRR abs/2406.13112 (2024)
• 2023
• 
  Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter K. Eastman, Thomas E. Markland, John D. Chodera, Gianni De Fabritiis:
  NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics. J. Chem. Inf. Model. 63(18): 5701-5708 (2023)
• 
  Yuanqing Wang, John D. Chodera:
  Spatial Attention Kinetic Networks with E(n)-Equivariance. ICLR 2023
• 
  Yuanqing Wang, John D. Chodera:
  Spatial Attention Kinetic Networks with E(n)-Equivariance. CoRR abs/2301.08893 (2023)
• 
  Yuanqing Wang, Iván Pulido, Kenichiro Takaba, Benjamin Kaminow, Jenke Scheen, Lily Wang, John D. Chodera:
  EspalomaCharge: Machine learning-enabled ultra-fast partial charge assignment. CoRR abs/2302.06758 (2023)
• 
  Kenichiro Takaba, Iván Pulido, Mike Henry, Hugo MacDermott-Opeskin, John D. Chodera, Yuanqing Wang:
  Espaloma-0.3.0: Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond. CoRR abs/2307.07085 (2023)
• 
  Peter K. Eastman, Raimondas Galvelis, Raúl P. Peláez, Charlles R. A. Abreu, Stephen E. Farr, Emilio Gallicchio, Anton Gorenko, Michael M. Henry, Frank Hu, Jing Huang, Andreas Krämer, Julien Michel, Joshua A. Mitchell, Vijay S. Pande, João P. G. L. M. Rodrigues, Jaime Rodríguez-Guerra, Andrew C. Simmonett, Jason M. Swails, Ivy Zhang, John D. Chodera, Gianni De Fabritiis, Thomas E. Markland:
  OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials. CoRR abs/2310.03121 (2023)
• 2022
• 
  Harold Grosjean, Mehtap Isik, Anthony Aimon, David L. Mobley, John D. Chodera, Frank von Delft, Philip C. Biggin:
  SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction. J. Comput. Aided Mol. Des. 36(4): 291-311 (2022)
• 
  Joshua T. Horton, Simon Boothroyd, Jeffrey Wagner, Joshua A. Mitchell, Trevor Gokey, David L. Dotson, Pavan Kumar Behara, Venkata Krishnan Ramaswamy, Mark Mackey, John D. Chodera, Jamshed Anwar, David L. Mobley, Daniel J. Cole:
  Open Force Field BespokeFit: Automating Bespoke Torsion Parametrization at Scale. J. Chem. Inf. Model. 62(22): 5622-5633 (2022)
• 
  Owen Madin, Simon Boothroyd, Richard A. Messerly, Josh Fass, John D. Chodera, Michael R. Shirts:
  Bayesian-Inference-Driven Model Parametrization and Model Selection for 2CLJQ Fluid Models. J. Chem. Inf. Model. 62(4): 874-889 (2022)
• 
  Raimondas Galvelis, Alejandro Varela-Rial, Stefan Doerr, Roberto Fino, Peter K. Eastman, Thomas E. Markland, John D. Chodera, Gianni De Fabritiis:
  NNP/MM: Fast molecular dynamics simulations with machine learning potentials and molecular mechanics. CoRR abs/2201.08110 (2022)
• 
  Peter K. Eastman, Pavan Kumar Behara, David L. Dotson, Raimondas Galvelis, John E. Herr, Josh T. Horton, Yuezhi Mao, John D. Chodera, Benjamin P. Pritchard, Yuanqing Wang, Gianni De Fabritiis, Thomas E. Markland:
  SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials. CoRR abs/2209.10702 (2022)
• 2021
• 
  Matthew N. Bahr, Aakankschit Nandkeolyar, John K. Kenna, Neysa Nevins, Luigi Da Vià, Mehtap Isik, John D. Chodera, David L. Mobley:
  Automated high throughput pK_a and distribution coefficient measurements of pharmaceutical compounds for the SAMPL8 blind prediction challenge. J. Comput. Aided Mol. Des. 35(11): 1141-1155 (2021)
• 
  Mehtap Isik, Ariën S. Rustenburg, Andrea Rizzi, Marilyn R. Gunner, David L. Mobley, John D. Chodera:
  Overview of the SAMPL6 pK_a challenge: evaluating small molecule microscopic and macroscopic pK_a predictions. J. Comput. Aided Mol. Des. 35(2): 131-166 (2021)
• 2020
• 
  Marilyn R. Gunner, Taichi Murakami, Ariën S. Rustenburg, Mehtap Isik, John D. Chodera:
  Standard state free energies, not pK_as, are ideal for describing small molecule protonation and tautomeric states. J. Comput. Aided Mol. Des. 34(5): 561-573 (2020)
• 
  Mehtap Isik, Teresa Danielle Bergazin, Thomas Fox, Andrea Rizzi, John D. Chodera, David L. Mobley:
  Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge. J. Comput. Aided Mol. Des. 34(4): 335-370 (2020)
• 
  Mehtap Isik, Dorothy Levorse, David L. Mobley, Timothy Rhodes, John D. Chodera:
  Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge. J. Comput. Aided Mol. Des. 34(4): 405-420 (2020)
• 
  Andrea Rizzi, Travis Jensen, David R. Slochower, Matteo Aldeghi, Vytautas Gapsys, Dimitris Ntekoumes, Stefano Bosisio, Michail Papadourakis, Niel M. Henriksen, Bert L. de Groot, Zoe Cournia, Alex Dickson, Julien Michel, Michael K. Gilson, Michael R. Shirts, David L. Mobley, John D. Chodera:
  The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations. J. Comput. Aided Mol. Des. 34(5): 601-633 (2020)
• 
  Steven K. Albanese, John D. Chodera, Andrea Volkamer, Simon Keng, Robert Abel, Lingle Wang:
  Is Structure-Based Drug Design Ready for Selectivity Optimization? J. Chem. Inf. Model. 60(12): 6211-6227 (2020)
• 
  Yuanqing Wang, Josh Fass, John D. Chodera:
  End-to-End Differentiable Molecular Mechanics Force Field Construction. CoRR abs/2010.01196 (2020)
• 2019
• 
  Mark James Abraham, Rossen Apostolov, Jonathan Barnoud, Paul Bauer, Christian Blau, Alexandre M. J. J. Bonvin, Matthieu Chavent, John D. Chodera, Karmen Condic-Jurkic, Lucie Delemotte, Helmut Grubmüller, Rebecca J. Howard, E. Joseph Jordan, Erik Lindahl, Samuli Ollila, Jana Selent, Daniel G. A. Smith, Phillip J. Stansfeld, Johanna K. S. Tiemann, Mikaël Trellet, Christopher J. Woods, Artem A. Zhmurov:
  Sharing Data from Molecular Simulations. J. Chem. Inf. Model. 59(10): 4093-4099 (2019)
• 
  Yuanqing Wang, Josh Fass, Chaya D. Stern, Kun Luo, John D. Chodera:
  Graph Nets for Partial Charge Prediction. CoRR abs/1909.07903 (2019)
• 2018
• 
  Josh Fass, David A. Sivak, Gavin E. Crooks, Kyle Beauchamp, Benedict J. Leimkuhler, John D. Chodera:
  Quantifying Configuration-Sampling Error in Langevin Simulations of Complex Molecular Systems. Entropy 20(5): 318 (2018)
• 
  Mehtap Isik, Dorothy Levorse, Ariën S. Rustenburg, Ikenna E. Ndukwe, Heather Wang, Xiao Wang, Mikhail Y. Reibarkh, Gary E. Martin, Alexey A. Makarov, David L. Mobley, Timothy Rhodes, John D. Chodera:
  pK a measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments. J. Comput. Aided Mol. Des. 32(10): 1117-1138 (2018)
• 
  Andrea Rizzi, Steven Murkli, John N. McNeill, Wei Yao, Matthew R. Sullivan, Michael K. Gilson, Michael Chiu, Lyle Isaacs, Bruce C. Gibb, David L. Mobley, John D. Chodera:
  Overview of the SAMPL6 host-guest binding affinity prediction challenge. J. Comput. Aided Mol. Des. 32(10): 937-963 (2018)
• 2017
• 
  Peter K. Eastman, Jason M. Swails, John D. Chodera, Robert McGibbon, Yutong Zhao, Kyle Beauchamp, Lee-Ping Wang, Andrew C. Simmonett, Matthew P. Harrigan, Chaya D. Stern, Rafal P. Wiewiora, Bernard R. Brooks, Vijay S. Pande:
  OpenMM 7: Rapid development of high performance algorithms for molecular dynamics. PLoS Comput. Biol. 13(7) (2017)
• 2016
• 
  Ariën S. Rustenburg, Justin Dancer, Baiwei Lin, Jianwen A. Feng, Daniel F. Ortwine, David L. Mobley, John D. Chodera:
  Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge. J. Comput. Aided Mol. Des. 30(11): 945-958 (2016)
• 
  Daniel L. Parton, Patrick B. Grinaway, Sonya M. Hanson, Kyle Beauchamp, John D. Chodera:
  Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale. PLoS Comput. Biol. 12(6) (2016)
• 2015
• 
  Sonya M. Hanson, Sean Ekins, John D. Chodera:
  Modeling error in experimental assays using the bootstrap principle: understanding discrepancies between assays using different dispensing technologies. J. Comput. Aided Mol. Des. 29(12): 1073-1086 (2015)

skipping 4 more matches