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HRA015357
   HRA015357.xlsx
Title:
Deep learning framework for precision lung cancer therapy: Integration of genomic sequencing and patient-derived organoids
Release date:
2025-12-12
Description:
This GSA supports the manuscript "Deep Learning Paradigm for Precision Lung Cancer Therapy with AI-Driven Genotype-Phenotype Mining and Patient-Derived Organoid Validation" (currently under submission). The study introduces a deep learning framework designed to predict drug responses in lung cancer patients by integrating patient genomic sequencing data with compound structural information.
Data Accessibility:   
Controlled access Request Data
BioProject:
PRJCA053170
Study type:
Disease Study
Disease name:
lung carcinoma
Data Access Committee

For each controlled access study, there is a corresponding Data Access Committee(DAC) to determine the access permissions. Access to actual data files is not managed by NGDC.


DAC NO.:
HDAC007678
DAC name:
Data access cmte for AIDD paper
Contact person:
Gu Zhongze
Email:
gu@seu.edu.cn
Description:
This is the data access committee for AIDD paper related datasets, which contains lung cancer patients next genomic sequencing data.
Individuals & samples
Files
Request Data
Submitter:   Gu Zhongze / gu@seu.edu.cn
Organization:   Southeast University
Submission date:   2025-12-11
Requests:   -