ProgModule: A novel computational framework to identify mutation driver modules for predicting cancer prognosis and immunotherapy response
Abstract Background Cancer originates from dysregulated cell proliferation driven by driver gene mutations. Despite numerous algorithms developed to identify genomic mutational signatures, they often suffer from high computational complexity and limited clinical applicability. Methods Here, we prese...
Saved in:
| Main Authors: | Xiangmei Li, Bingyue Pan, Xilong Zhao, Yinchun Su, Jiyin Lai, Siyuan Li, Yalan He, Jiashuo Wu, Junwei Han |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-05-01
|
| Series: | Journal of Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12967-025-06497-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
iPRISM: Intelligent Predicting Response to Cancer Immunotherapy through Systematic Modeling
by: Yinchun Su, et al.
Published: (2025-06-01) -
CITMIC: Comprehensive Estimation of Cell Infiltration in Tumor Microenvironment based on Individualized Intercellular Crosstalk
by: Xilong Zhao, et al.
Published: (2025-01-01) -
DeepCCDS: Interpretable Deep Learning Framework for Predicting Cancer Cell Drug Sensitivity through Characterizing Cancer Driver Signals
by: Jiashuo Wu, et al.
Published: (2025-06-01) -
Proving Properties of Dekker’s Algorithm for Mutual Exclusion of N Processes
by: Libero Nigro, et al.
Published: (2025-04-01) -
Clinical efficacy analysis of cross-line immunotherapy in driver gene-negative advanced non-small cell lung cancer patients
by: WANG Yuankun, et al.
Published: (2025-02-01)