A Deep Learning Framework Identifies Pathogenic Noncoding Somatic Mutations from Personal Prostate Cancer Genomes-Reference-Cited by-同舟云学术

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A Deep Learning Framework Identifies Pathogenic Noncoding Somatic Mutations from Personal Prostate Cancer Genomes

Published:2020-09-09 Issue:21 Volume:80 Page:4644-4654
ISSN:0008-5472
Container-title:Cancer Research
language:en
Short-container-title:Cancer Res

Author:

Wang Cheng,Li Jingjing^ORCID

Funder

UCSF Prostate Cancer Program Pilot Research Funding Award

UC | UCSF | School of Medicine, University of California, San Francisco

Publisher

American Association for Cancer Research (AACR)

Subject

Cancer Research,Oncology

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Integrative identification of non-coding regulatory regions driving metastatic prostate cancer;Cell Reports;2024-09

2. Integrative analysis of noncoding mutations identifies the druggable genome in preterm birth;Science Advances;2024-01-19

3. Assessment of Prostate and Bladder Cancer Genomic Biomarkers Using Artificial Intelligence: a Systematic Review;Current Urology Reports;2023-12-15

4. The Diagnostic Landscape of Adult Neurogenetic Disorders;Biology;2023-11-22

5. Attention-based generative adversarial networks improve prognostic outcome prediction of cancer from multimodal data;Briefings in Bioinformatics;2023-09-22

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