Multiplex Networks and Pan-Cancer Multiomics-Based Driver Gene Identification Using Graph Neural Networks
Identifying cancer driver genes has paramount significance in elucidating the intricate mechanisms underlying cancer development, progression, and therapeutic interventions. Abundant omics data and interactome networks provided by numerous extensive databases enable the application of graph deep lea...
Saved in:
| Main Authors: | Xingyi Li, Junming Li, Jun Hao, Xingyu Liao, Min Li, Xuequn Shang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2024-12-01
|
| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2024.9020043 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
MONet: cancer driver gene identification algorithm based on integrated analysis of multi-omics data and network models
by: Yingzan Ren, et al.
Published: (2025-02-01) -
Network-based analyses of multiomics data in biomedicine
by: Rachit Kumar, et al.
Published: (2025-05-01) -
Comprehensive pan-cancer analysis indicates key gene of p53-independent apoptosis is a novel biomarker for clinical application and chemotherapy in colorectal cancer
by: Jianing Yan, et al.
Published: (2025-03-01) -
Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for thyroid cancer
by: Peng Zhang, et al.
Published: (2025-06-01) -
Screening and bioinformatics analysis of a ceRNA network based on the circular RNAs, miRNAs, and mRNAs in pan‐cancer
by: Zhanghan Chen, et al.
Published: (2020-10-01)