Shen(申) Wan Xiang, Charles

Shen(申) Wan Xiang, Charles

Postdoctoral Fellow at HMS

Publications

Deep learning of 2D-Restructured gene expression representations for improved low-sample therapeutic response prediction

Published in Computers in Biology and Medicine, 2023

Deep learning for therapeutic response prediction

Cheng K P*, Shen W X*, Jiang Y Y, et al. Deep learning of 2D-Restructured gene expression representations for improved low-sample therapeutic response prediction[J]. Computers in Biology and Medicine, 2023, 164: 107245. https://www.sciencedirect.com/science/article/abs/pii/S0010482523007102

Enhanced metagenomic deep learning for disease prediction and consistent signature recognition by restructured microbiome 2D representations

DOI PyPI version Example Colab

Published in Cell Press Patterns, 2023

2D-Representations for metagenomic data deep learning

Shen W X, Liang S R, Jiang Y Y, et al. Enhanced metagenomic deep learning for disease prediction and consistent signature recognition by restructured microbiome 2D representations[J]. Patterns, 2023, 4(1): 100658. https://www.cell.com/patterns/fulltext/S2666-3899(22)00298-7

AggMapNet: Enhanced and Explainable Low-Sample Omics Deep Learning with Feature-Aggregated Multi-Channel Networks

DOI Example PyPI version Documentation Status Downloads

Published in Nucleic Acids Research, 2022

AggMapNet for Omics-based disease prediction and key biomarker discovery

Recommended citation: Shen W X, Liu Y, Chen Y, et al. AggMapNet: Enhanced and Explainable Low-Sample Omics Deep Learning with Feature-Aggregated Multi-Channel Networks[J]. Nucleic Acids Research., 2022, 50(8): e45-e45. https://academic.oup.com/nar/article/50/8/e45/6517966

Out-of-the-box deep learning prediction of pharmaceutical properties by broadly learned knowledge-based molecular representations

License: MIT DOI Codeocean Paper PyPI version Documentation Status Build Status

Published in Nature Machine Intelligence, 2021

2D-Representations for small molecular deep learning and property prediction

Recommended citation: Shen W X, Zeng X, Zhu F, et al. Out-of-the-box deep learning prediction of pharmaceutical properties by broadly learned knowledge-based molecular representations[J]. Nature Machine Intelligence, 2021, 3(4): 334-343. https://www.nature.com/articles/s42256-021-00301-6

High-Content Phenotypic Screen of a Focused TCAMS Drug Library Identifies Novel Disruptors of the Malaria Parasite Calcium Dynamics

Published in ACS Chemical Biology, 2021

Phenotypic Screen of samll molecules that for Malaria

Recommended citation: Chia, W., Gomez-Lorenzo, M. G., Castellote, I., Tong, J. X., Chandramohanadas, R., Thu Chu, T. T., Shen, W. X., ... & Tan, K. S. High-Content Phenotypic Screen of a Focused TCAMS Drug Library Identifies Novel Disruptors of the Malaria Parasite Calcium Dynamics. ACS Chemical Biology, 2021, 16(11), 2348-2372 https://pubs.acs.org/doi/pdf/10.1021/acschembio.1c00512

Predicting Enzymatic Hydrolysis Half-lives of New Chemicals Using Support Vector Regression Models Based on Stepwise Feature Elimination

Published in Molecular Informatics, 2017

Predicting Enzymatic Hydrolysis Half-lives of New Chemicals Using Support Vector Regression Models Based on Stepwise Feature Elimination

Recommended citation: Shen W X, Xiao T, Chen S, et al. Predicting the Enzymatic Hydrolysis Half‐lives of New Chemicals Using Support Vector Regression Models Based on Stepwise Feature Elimination[J]. Molecular informatics, 2017, 36(11): 1600153. https://onlinelibrary.wiley.com/doi/10.1002/minf.201600153