Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
July 1, 2024Journal of Cellular and Molecular MedicineOpen Access

Deciphering the tumour microenvironment of clear cell renal cell carcinoma: Prognostic insights from programmed death genes using machine learning

View Full Paper
Ask AI
Bookmark
Share

Authors

HTHongtao TuQHQingwen HuYMYuying Ma

Discussion

Loading...

Member takes

Overview

Key Points

Key points are not available for this paper at this time.

Cite This Study

Tu et al. (2024) studied this question.

synapsesocial.com/papers/68e61ca7b6db6435875af14fhttps://doi.org/10.1111/jcmm.18524
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1An Integrated Machine Learning Framework Identifies Prognostic Gene Pair Biomarkers Associated with Programmed Cell Death Modalities in Clear Cell Renal Cell Carcinoma2024 · 5 citations
  2. 2Assessing the role of programmed cell death signatures and related gene TOP2A in progression and prognostic prediction of clear cell renal cell carcinoma2024 · 13 citations
  3. 3Comprehensive investigation of malignant epithelial cell-related genes in clear cell renal cell carcinoma: development of a prognostic signature and exploration of tumor microenvironment interactions2024 · 4 citations
  4. 4Clinical value and in vitro validation of gene and molecular subtype identification in renal clear cell carcinoma2025
  5. 5Identification of Molecular Signatures and Prognostic Markers in Clear Cell Renal Cell Carcinoma through Advanced Bioinformatics and Systems Biology2025