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Simone Sciabola
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Journal Articles
- 2024
- [j7]Zhonglin Cao
, Simone Sciabola
, Ye Wang
:
Large-Scale Pretraining Improves Sample Efficiency of Active Learning-Based Virtual Screening. J. Chem. Inf. Model. 64(6): 1882-1891 (2024) - 2023
- [j6]Cheng Fang
, Ye Wang, Richard Grater, Sudarshan Kapadnis
, Cheryl Black, Patrick E. Trapa, Simone Sciabola
:
Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective. J. Chem. Inf. Model. 63(11): 3263-3274 (2023) - 2016
- [j5]Qin Wang, Simone Sciabola, Gabriela Barreiro, Xinjun Hou, Guoyun Bai, Michael J. Shapiro, Frank Koehn, Anabella Villalobos, Matthew P. Jacobson
:
Dihedral Angle-Based Sampling of Natural Product Polyketide Conformations: Application to Permeability Prediction. J. Chem. Inf. Model. 56(11): 2194-2206 (2016) - 2010
- [j4]Simone Sciabola, Robert V. Stanton, James E. J. Mills, Maria M. Flocco, Massimo Baroni
, Gabriele Cruciani
, Francesca Perruccio, Jonathan S. Mason:
High-Throughput Virtual Screening of Proteins Using GRID Molecular Interaction Fields. J. Chem. Inf. Model. 50(1): 155-169 (2010) - 2008
- [j3]Simone Sciabola, Robert V. Stanton, Sarah Wittkopp, Scott A. Wildman
, Deborah J. Moshinsky, Shobha Potluri, Hualin Xi:
Predicting Kinase Selectivity Profiles Using Free-Wilson QSAR Analysis. J. Chem. Inf. Model. 48(9): 1851-1867 (2008) - 2007
- [j2]Simone Sciabola, Iñaki Morao, Marcel J. de Groot:
Pharmacophoric Fingerprint Method (TOPP) for 3D-QSAR Modeling: Application to CYP2D6 Metabolic Stability. J. Chem. Inf. Model. 47(1): 76-84 (2007) - [j1]Massimo Baroni
, Gabriele Cruciani
, Simone Sciabola, Francesca Perruccio, Jonathan S. Mason:
A Common Reference Framework for Analyzing/Comparing Proteins and Ligands. Fingerprints for Ligands And Proteins (FLAP): Theory and Application. J. Chem. Inf. Model. 47(2): 279-294 (2007)
Informal and Other Publications
- 2024
- [i3]Albert Bou, Morgan Thomas, Sebastian Dittert, Carles Navarro Ramírez, Maciej Majewski, Ye Wang, Shivam Patel, Gary Tresadern, Mazen Ahmad, Vincent Moens, Woody Sherman, Simone Sciabola, Gianni De Fabritiis:
ACEGEN: Reinforcement learning of generative chemical agents for drug discovery. CoRR abs/2405.04657 (2024) - 2023
- [i2]Zhonglin Cao, Simone Sciabola, Ye Wang:
Large-scale Pretraining Improves Sample Efficiency of Active Learning based Molecule Virtual Screening. CoRR abs/2309.11687 (2023) - 2022
- [i1]Wenlu Wang, Ye Wang, Honggang Zhao, Simone Sciabola:
A Transformer-based Generative Model for De Novo Molecular Design. CoRR abs/2210.08749 (2022)
Coauthor Index
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