工作流程
计算机科学
个性化医疗
背景(考古学)
仿形(计算机编程)
鉴定(生物学)
数据科学
计算生物学
注释
原始数据
精确肿瘤学
精密医学
医学物理学
生物信息学
医学
人工智能
生物
病理
数据库
操作系统
古生物学
程序设计语言
植物
标识
DOI:10.1016/j.semcancer.2020.12.020
摘要
High-throughput molecular profiling of tumors is a fundamental aspect of precision oncology, enabling the identification of genomic alterations that can be targeted therapeutically. In this context, a patient is matched to a specific drug or therapy based on the tumor's underlying genetic driver events rather than the histologic classification. This approach requires extensive bioinformatics methodology and workflows, including raw sequencing data processing and quality control, variant calling and annotation, integration of different molecular data types, visualization and finally reporting the data to physicians, cancer researchers and pharmacologists in a format that is readily interpretable for clinical decision making. This review comprises a broad overview of these bioinformatics aspects and discusses the multiple analytical, technical and interpretational challenges that remain to efficiently translate molecular findings into personalized treatment recommendations.
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