论文标题
综合数据分析框架以增强癌症精度医学
Integrative Data Analytic Framework to Enhance Cancer Precision Medicine
论文作者
论文摘要
随着高通量生物技术的发展，我们越来越多地积累了有关疾病，尤其是癌症的生物医学数据。需要计算模型和方法来筛选，整合和从各种可用数据中提取新知识，以提高对疾病和患者护理的机械理解。为了发现特定癌症类型的分子机制和药物适应症，我们开发了一个综合框架，能够利用各种各样的分子和泛伴侣数据。我们表明，我们的方法表现优于竞争方法，并且可以确定新的关联。此外，通过数据源的联合整合，我们的框架还可以发现癌症类型与没有可用知识的分子实体之间的联系。我们的新框架很灵活，可以轻松重新重新制定以研究任何生物医学问题。
With the advancement of high-throughput biotechnologies, we increasingly accumulate biomedical data about diseases, especially cancer. There is a need for computational models and methods to sift through, integrate, and extract new knowledge from the diverse available data to improve the mechanistic understanding of diseases and patient care. To uncover molecular mechanisms and drug indications for specific cancer types, we develop an integrative framework able to harness a wide range of diverse molecular and pan-cancer data. We show that our approach outperforms competing methods and can identify new associations. Furthermore, through the joint integration of data sources, our framework can also uncover links between cancer types and molecular entities for which no prior knowledge is available. Our new framework is flexible and can be easily reformulated to study any biomedical problems.
