Supplementary Tables S3, S5 and S6 for "Machine Learning–Driven Integration of Cancer Cell Phenotypes Predicts Cisplatin Sensitivity"

Overview - Supplementary Table S3.xlsx, List of cell lines included in the analyses. - Supplementary Table S5.xlsx, Differential expression analysis results between cluster 2 (resistant) and cluster 4 (sensitive) using pyDESeq2. - Supplementary Table S6.xlsx, SHAP values per gene derived from the machine learning model. Keywords cisplatin, machine learning, omics, RNAseq, SHAP, LightGBM, TCGA

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-20
DOI
https://doi.org/10.5281/zenodo.16786026
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00
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article

Supplementary Tables S3, S5 and S6 for "Machine Learning–Driven Integration of Cancer Cell Phenotypes Predicts Cisplatin Sensitivity"

Zenodo (CERN European Organization for Nuclear Research)
Ferroptosis and cancer prognosis
article

Supplementary Tables S3, S5 and S6 for "Machine Learning–Driven Integration of Cancer Cell Phenotypes Predicts Cisplatin Sensitivity"

article en

Abstract

Overview - Supplementary Table S3.xlsx, List of cell lines included in the analyses. - Supplementary Table S5.xlsx, Differential expression analysis results between cluster 2 (resistant) and cluster 4 (sensitive) using pyDESeq2. - Supplementary Table S6.xlsx, SHAP values per gene derived from the machine learning model. Keywords cisplatin, machine learning, omics, RNAseq, SHAP, LightGBM, TCGA

Zenodo (CERN European Organization for Nuclear Research)
Iwate Medical University (JP)
Openalex Percentile: Top 36%
Ferroptosis and cancer prognosis
DOIOpen Access PDFOpenAlex
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Supplementary Tables S3, S5 and S6 for "Machine Learning–Driven Integration of Cancer Cell Phenotypes Predicts Cisplatin Sensitivity" · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS