MosGraphGen: A novel tool to generate multi-omics signaling graphs to facilitate integrative and interpretable graph AI model development

Authors

• Heming Zhang, Washington University School of Medicine in St. Louis
• Dekang Cao, Washington University School of Medicine in St. Louis
• Zirui Chen, Washington University School of Medicine in St. Louis
• Xiuyuan Zhang, Washington University School of Medicine in St. Louis
• Yixin Chen, Washington University in St. Louis
• Cole Sessions, Washington University School of Medicine in St. Louis
• Carlos Cruchaga, Washington University School of Medicine in St. Louis
• Philip Payne, Washington University School of Medicine in St. Louis
• Guangfu Li, Washington University School of Medicine in St. Louis
• Michael Province, Washington University School of Medicine in St. Louis
• Fuhai Li, Washington University School of Medicine in St. Louis

Journal

Bioinformatics Advances

Publication Date

1-1-2024

Volume

4

Issue

1

First Page

vbae151

Document Type

Open Access Publication

DOI

10.1093/bioadv/vbae151

Rights and Permissions

Heming Zhang, Dekang Cao, Zirui Chen, Xiuyuan Zhang, Yixin Chen, Cole Sessions, Carlos Cruchaga, Philip Payne, Guangfu Li, Michael Province, Fuhai Li, mosGraphGen: a novel tool to generate multi-omics signaling graphs to facilitate integrative and interpretable graph AI model development, Bioinformatics Advances, Volume 4, Issue 1, 2024, vbae151, https://doi.org/10.1093/bioadv/vbae151. https://academic.oup.com/bioinformaticsadvances/article/4/1/vbae151/7815723?login=true. © The Author(s) 2024. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Recommended Citation

Zhang, Heming; Cao, Dekang; Chen, Zirui; Zhang, Xiuyuan; Chen, Yixin; Sessions, Cole; Cruchaga, Carlos; Payne, Philip; Li, Guangfu; Province, Michael; and Li, Fuhai, "MosGraphGen: A novel tool to generate multi-omics signaling graphs to facilitate integrative and interpretable graph AI model development." Bioinformatics Advances. 4, 1. vbae151 (2024).
https://digitalcommons.wustl.edu/oa_4/7688

Department

ICTS (Institute of Clinical and Translational Sciences)