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Integration of Complex Data Sources to Provide Biologic Insight into Pulmonary Vascular Disease (2015 Grover Conference Series):

机译:集成复杂数据源以提供对肺血管疾病的生物学见解(2015年格罗弗会议系列):

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The application of complex data sources to pulmonary vascular diseases is an emerging and promising area of investigation. The use of -omics platforms, in silico modeling of gene networks, and linkage of large human cohorts with DNA biobanks are beginning to bear biologic insight into pulmonary hypertension. These approaches to high-throughput molecular phenotyping offer the possibility of discovering new therapeutic targets and identifying variability in response to therapy that can be leveraged to improve clinical care. Optimizing the methods for analyzing complex data sources and accruing large, well-phenotyped human cohorts linked to biologic data remain significant challenges. Here, we discuss two specific types of complex data sources—gene regulatory networks and DNA-linked electronic medical record cohorts—that illustrate the promise, challenges, and current limitations of these approaches to understanding and managing pulmonary vascular disease.
机译:复杂数据源在肺血管疾病中的应用是一个新兴且有希望的研究领域。 -omics平台的使用,基因网络的计算机模拟以及大型人群与DNA生物库的联系开始对肺动脉高压具有生物学的认识。这些高通量分子表型的方法提供了发现新的治疗靶标并鉴定对治疗反应的变异性的可能性,可以利用这些变异性来改善临床护理。优化分析复杂数据源的方法并增加与生物学数据相关的表型良好的大型人群仍然是重大挑战。在这里,我们讨论两种特定类型的复杂数据源-基因调控网络和与DNA相关的电子病历组群-阐明了理解和管理肺血管疾病的这些方法的前景,挑战和当前局限性。

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