Harvard Training Program in Bioinformatics Applied to Diabetes, Obesity and Metabolism.

摘要 在过去十年中，我们见证了变革性的技术和分析进步。 它可以以全局方式查询生物系统，通常跨越 分子光谱。对基因、基因标记、转录本、蛋白质、 小分子，它们的相互作用产生了巨大的数据集，反映了 特定的代谢、发育或组织状态。这项活动在#年越来越可行。 与疾病最相关的生物体，人类：当与丰富的临床和 可在观察队列、临床试验或电子版中获得的表型信息 病历，可以做出巨大的推论来获得病理生理学的洞察。 这类活动产生了大量与2型糖尿病、肥胖症和 相关的代谢特征。迫切需要吸引在以下领域有经验的调查人员 数学、统计学、计算生物学和生物信息学来分析和 对这些数据的解释，并为对这些数据感兴趣的调查人员提供装备 具有提取有价值的知识所需的工具和技能的表型。在这项提案中，我们 已经组建了一个由30多名经验丰富的调查人员组成的团队，整个哈佛系统 在每一项相关技能方面拥有尖端能力，并在过去的记录中 支持在代谢性疾病中申报的利益。这笔培训补助金将利用他们的 通过资助8名选定的受训人员，为他们提供专门的 指导，并将他们与能够在 与NIDDK感兴趣的疾病相关的多学科环境。

ABSTRACT Over the past decade we have witnessed transformative technological and analytical advances which can query biological systems in a global manner, typically across a select axis in the molecular spectrum. The comprehensive study of genes, gene marks, transcripts, proteins, small molecules, and their interactions have generated enormous data sets that reflect a specific metabolic, developmental or tissue state. Increasingly this activity has been feasible in the organism most relevant to disease, the human: when coupled with the rich clinical and phenotyping information available in observational cohorts, clinical trials or the electronic medical record, tremendous inferences can be made to derive pathophysiological insight. This type of activity has produced a trove of information relevant to type 2 diabetes, obesity and related metabolic traits. There is an urgent need to attract investigators experienced in mathematics, statistics, computational biology and bioinformatics to the analysis and interpretations of such data, and to equip investigators who have an interest in these phenotypes with the tools and skills required to extract valuable knowledge. In this proposal, we have assembled a team of three dozen accomplished investigators across the Harvard system who have cutting-edge capabilities in each of the pertinent skill sets, and whose track record supports a declared interest in metabolic disease. This training grant will leverage their complementary expertise by funding eight selected trainees, providing them with dedicated instruction, and pairing them with faculty mentors who can provide rigorous training in a multidisciplinary setting pertinent to diseases of interest to the NIDDK.