Ye Wang

16 papers Journal 16
YearRankTypeTitle / Venue / Authors
2026 J jnl
Correction to "ROSHAMBO2: Accelerating Molecular Alignment for Large Chemical Libraries with GPU Optimization and Algorithmic Advances".
J. Chem. Inf. Model.
Rasha Atwi, Stephen E. Farr, Ye Wang, Adam Antoszewski, Simone Sciabola
2025 J jnl
Iterative Foundation Model Fine-Tuning on Multiple Rewards.
CoRR
Pouya M. Ghari, Simone Sciabola, Ye Wang
2025 J jnl
ROSHAMBO2: Accelerating Molecular Alignment for Large Chemical Libraries with GPU Optimization and Algorithmic Advances.
J. Chem. Inf. Model.
Rasha Atwi, Stephen E. Farr, Ye Wang, Adam Antoszewski, Simone Sciabola
2024 J jnl
ACEGEN: Reinforcement Learning of Generative Chemical Agents for Drug Discovery.
J. Chem. Inf. Model.
Albert Bou, Morgan C. Thomas, Sebastian Dittert, Carles Navarro, Maciej Majewski, Ye Wang, Shivam Patel, Gary Tresadern, Mazen Ahmad, Vincent Moens, Woody Sherman, Simone Sciabola, Gianni De Fabritiis
2024 J jnl
ACEGEN: Reinforcement learning of generative chemical agents for drug discovery.
CoRR
Albert Bou, Morgan C. 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
2024 J jnl
Large-Scale Pretraining Improves Sample Efficiency of Active Learning-Based Virtual Screening.
J. Chem. Inf. Model.
Zhonglin Cao, Simone Sciabola, Ye Wang
2024 J jnl
ROSHAMBO: Open-Source Molecular Alignment and 3D Similarity Scoring.
J. Chem. Inf. Model.
Rasha Atwi, Ye Wang, Simone Sciabola, Adam Antoszewski
2023 J jnl
Large-scale Pretraining Improves Sample Efficiency of Active Learning based Molecule Virtual Screening.
CoRR
Zhonglin Cao, Simone Sciabola, Ye Wang
2023 J jnl
Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective.
J. Chem. Inf. Model.
Cheng Fang, Ye Wang, Richard Grater, Sudarshan Kapadnis, Cheryl Black, Patrick E. Trapa, Simone Sciabola
2022 J jnl
A Transformer-based Generative Model for De Novo Molecular Design.
CoRR
Wenlu Wang, Ye Wang, Honggang Zhao, Simone Sciabola
2022 J jnl
DeepPerVar: a multi-modal deep learning framework for functional interpretation of genetic variants in personal genome.
Bioinform.
Ye Wang, Li Chen
2022 J jnl
Exploiting deep transfer learning for the prediction of functional non-coding variants using genomic sequence.
Bioinform.
Li Chen, Ye Wang, Fengdi Zhao
2022 J jnl
Performance modeling for I/O-intensive applications on virtual machines.
Concurr. Comput. Pract. Exp.
Tathagata Bhattacharya, Xiaopu Peng, Jianzhou Mao, Chaowei Zhang, Taha Takreeti, Ye Wang, Ting Cao, Xiao Qin
2021 J jnl
A novel deep learning method for predictive modeling of microbiome data.
Briefings Bioinform.
Ye Wang, Tathagata Bhattacharya, Yuchao Jiang, Xiao Qin, Yue Wang, Yunlong Liu, Andrew J. Saykin, Li Chen
2021 J jnl
WEVar: a novel statistical learning framework for predicting noncoding regulatory variants.
Briefings Bioinform.
Ye Wang, Yuchao Jiang, Bing Yao, Kun Huang, Yunlong Liu, Yue Wang, Xiao Qin, Andrew J. Saykin, Li Chen
2019 J jnl
TIVAN: tissue-specific cis-eQTL single nucleotide variant annotation and prediction.
Bioinform.
Li Chen, Ye Wang, Bing Yao, Amit Mitra, Xu Wang, Xiao Qin