Ye Wang

According to our database, Ye Wang authored at least 16 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Advancing Ligand-based Virtual Screening and Molecular Generation with Pretrained Molecular Embedding Distance.

Shiyun Wa, Yifei Wang, Simone Sciabola, Ye Wang

CoRR, April, 2026

Correction to "ROSHAMBO2: Accelerating Molecular Alignment for Large Chemical Libraries with GPU Optimization and Algorithmic Advances".

Rasha Atwi, Stephen E. Farr, Ye Wang, Adam Antoszewski, Simone Sciabola

J. Chem. Inf. Model., 2026

2025

ROSHAMBO2: Accelerating Molecular Alignment for Large Chemical Libraries with GPU Optimization and Algorithmic Advances.

Rasha Atwi, Stephen E. Farr, Ye Wang, Adam Antoszewski, Simone Sciabola

J. Chem. Inf. Model., 2025

Iterative Foundation Model Fine-Tuning on Multiple Rewards.

Pouya M. Ghari, Simone Sciabola, Ye Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Large-Scale Pretraining Improves Sample Efficiency of Active Learning-Based Virtual Screening.

Zhonglin Cao, Simone Sciabola, Ye Wang

J. Chem. Inf. Model., 2024

ACEGEN: Reinforcement Learning of Generative Chemical Agents for Drug Discovery.

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

J. Chem. Inf. Model., 2024

ROSHAMBO: Open-Source Molecular Alignment and 3D Similarity Scoring.

Rasha Atwi, Ye Wang, Simone Sciabola, Adam Antoszewski

J. Chem. Inf. Model., 2024

2023

Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective.

Cheng Fang, Ye Wang, Richard Grater, Sudarshan Kapadnis, Cheryl Black, Patrick E. Trapa, Simone Sciabola

J. Chem. Inf. Model., June, 2023

Large-scale Pretraining Improves Sample Efficiency of Active Learning based Molecule Virtual Screening.

Zhonglin Cao, Simone Sciabola, Ye Wang

CoRR, 2023

2022

DeepPerVar: a multi-modal deep learning framework for functional interpretation of genetic variants in personal genome.

Ye Wang, Li Chen

Bioinform., December, 2022

A Transformer-based Generative Model for De Novo Molecular Design.

Wenlu Wang, Ye Wang, Honggang Zhao, Simone Sciabola

CoRR, 2022

Performance modeling for I/O-intensive applications on virtual machines.

Tathagata Bhattacharya, Xiaopu Peng, Jianzhou Mao, Chaowei Zhang, Taha Takreeti, Ye Wang, Ting Cao, Xiao Qin

Concurr. Comput. Pract. Exp., 2022

Exploiting deep transfer learning for the prediction of functional non-coding variants using genomic sequence.

Li Chen, Ye Wang, Fengdi Zhao

Bioinform., 2022

2021

WEVar: a novel statistical learning framework for predicting noncoding regulatory variants.

Ye Wang, Yuchao Jiang, Bing Yao, Kun Huang, Yunlong Liu, Yue Wang, Xiao Qin, Andrew J. Saykin, Li Chen

Briefings Bioinform., 2021

A novel deep learning method for predictive modeling of microbiome data.

Ye Wang, Tathagata Bhattacharya, Yuchao Jiang, Xiao Qin, Yue Wang, Yunlong Liu, Andrew J. Saykin, Li Chen

Briefings Bioinform., 2021

2019

TIVAN: tissue-specific cis-eQTL single nucleotide variant annotation and prediction.

Li Chen, Ye Wang, Bing Yao, Amit Mitra, Xu Wang, Xiao Qin

Bioinform., 2019