WMRCA + : a weighted majority rule-based clustering method for cancer subtype prediction using metabolic gene sets
Abstract Accurate classification of cancer subtypes plays a pivotal role in advancing precision medicine. In this study, we introduce WMRCA + , a novel clustering approach based on a weighted majority rule that integrates multi-omics data and incorporates metabolic gene sets to robustly determine th...
Saved in:
| Main Authors: | Guojun Liu, Zhaopo Zhu, Yongqiang Xing, Hu Meng, Khyber Shinwari, Ningkun Xiao, Guoqing Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | Hereditas |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s41065-025-00487-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Identification of The Immune Subtype Among Muscle-invasive Bladder Cancer Patients by Multiple Datasets
by: Khyber Shinwari, et al.
Published: (2022-04-01) -
Systematic screening of metabolic pathways to identify two breast cancer subtypes with divergent immune characteristics
by: Xiangshu Cheng, et al.
Published: (2025-07-01) -
Hepatotoxicity in Carp (<i>Carassius auratus</i>) Exposed to Perfluorooctane Sulfonate (PFOS): Integrative Histopathology and Transcriptomics Analysis
by: Lin Tang, et al.
Published: (2025-02-01) -
Metabolic reprogramming in hepatocellular carcinoma: an integrated omics study of lipid pathways and their diagnostic potential
by: Peng Dai, et al.
Published: (2025-06-01) -
Construction of lung adenocarcinoma subtype and prognosis model based on fatty acid metabolism-related genes
by: Jing Chen, et al.
Published: (2025-05-01)