Traditional mutation assessment methods generally focus on predicting disruptive changes in protein-coding regions rather than non-coding regulatory regions like untranslated regions (UTRs) of mRNAs.

NIAID Data Ecosystem60

Advanced NSCLC Cohort: Clinical Characteristics and cfDNA Mutation Dataset

肿瘤液体活检

肺癌基因研究

This dataset comprises anonymized clinical variables and circulating free DNA (cfDNA) mutation data from patients diagnosed with advanced non–small cell lung cancer (NSCLC). It encompasses demographic

Zenodo2025-12-11 更新30

NSCLC data

肺癌基因研究

精准医学研究

The study incorporated RNA-sequencing (RNA-seq) and whole-exome sequencing (WES) data from 38 patients with non-small cell lung cancer (NSCLC), along with relevant clinical data.

NIAID Data Ecosystem60

ena-DATASET-UniCal-01-05-2020-00:40:53:266-485 - samples

肺癌基因研究

活检技术

The plasma samples and white blood cell samples were collected from 30 non-small-cell lung cancer patients and 3 healthy individuals. The solid tumor biopsy samples from 14 patients (a subset of the 3

NIAID Data Ecosystem60

ena-DATASET-BGI-18-06-2015-05:57:10:511-19 - samples

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