Data Science Training: the Essentials

项目摘要 在过去的40年里，联邦政府在与病态疾病的斗争中投入了各种各样的资金。 HIV-1的后果给人们带来了治愈的希望。但这些 目前生活和老龄化的艾滋病毒感染者继续呈现出削弱健康的影响， 对生活质量产生负面影响。在神经系统并发症的背景下，艾滋病毒感染者- 1还可能患有心血管、肺、骨骼和肾脏疾病， 尽管抗逆转录病毒疗法成功地预防了艾滋病， 传输通过国家数据中心等长期资源利用大数据 生物技术信息中心（NCBI），以及包括NIH All of Us在内的更新来源 倡议将越来越广泛地被包括在内，并用于检验关键假设， 其中许多来自实验室研究。正如最近的NIH报告中所讨论的， 数据科学的战略计划，快速的技术进步和收集大量的 大量的基因组和基因表达以及其他类型的生物数据， 认识到生物医学研究人员对各种数据库/储存库的了解， 在正确处理，分析，存储，共享和报告调查结果的方式， 严格和传播新知识，将是重要的，以改善人类健康， 更快的幸福。在这方面，我们最近组装了一个由 神经科学系讨论如何加强计算训练 为博士预科生和博士生提供科学培训。研究结果之一是， 讨论是，考虑到事先准备/暴露的不同程度， 学员探索计算神经科学中更先进概念的能力， 指导如何将工具应用于行为的科学调查。对于我们目前 资助R25，我们通过讲座向博士前学员介绍计算神经科学。 在拟议的补充，我们将提供一个更深入的沉浸通过四个相互关联的 通过面对面和虚拟方式相结合提供的课程模块， 最大限度地利用10周的夏季培训时间。

Project Summary Federal investments of all types over the last 40 years in the battle against the pathological consequences of HIV-1 have given hope that a cure will soon be realized. However, those currently living and aging with HIV continue to present with debilitating health impacts that negatively affect quality of life. In the context of the neurological complications, people with HIV- 1 can also suffer from cardiovascular, pulmonary, bone and kidney disease revealing that multiple body systems continue to be impacted despite anti-retroviral therapy successful in preventing transmission. Harnessing Big Data available through longstanding resources like the National Center for Biotechnology Information (NCBI), and newer sources including the NIH All of Us Initiative will increasingly be more widely included and used for testing of critical hypotheses, many which emerge from laboratory-based research. As discussed in the recent NIH report on the strategic plan for data science, the rapid technological advances and collection of vast amounts of genomic and gene expression and other types of biologic data, it has been long recognized that for biomedical researchers knowledge about varied databanks/repositories, and expertise in the proper handling, analysis, storage, sharing, and reporting of findings in ways that are rigorous and disseminate new knowledge, will be important to improve human health and well-being in a more rapid fashion. In this regard, we recently assembled a workgroup made of faculty in the neurological sciences to discuss how to strengthen training in computational sciences for predoctoral and doctoral trainees. One of the findings that emerged from the discussion was, given the varying degrees of prior preparation/exposure there is disparity in trainees’ ability to explore more advanced concepts in computational neuroscience and little instruction on how to apply the tools to scientific investigations of behavior. For our currently funded R25, we introduced predoctoral trainees to computational neuroscience through lectures. In the proposed supplement we would provide a deeper immersion through four inter-related course modules delivered through a combination of in-person and virtual modalities that maximizes the 10-week summer training period.