Mayo Clinic Research Education Program in Computational Autonomic Neurobiology of Diabetes and Digestive and Kidney Diseases

项目摘要/摘要 现代生物医学科学和医学，拥有大量不同和复杂的数据集，需要 我们教育模式的范式转变，以培养下一代科学家和医生 能够进行和解释计算分析。目前的教育模式有 在计算数据科学家和面向疾病的专家之间造成了严重的专业差距 生理学家。这项建议的具体目的是建立创新的教育模式，以 促进计算技能的培训，以便立即和直接应用于研究 体验并创造下一代生物医学科学家以领导新发现 以糖尿病、消化和肾脏疾病为导向的研究。梅奥诊所的研究性教育 计算自主神经生物学课程是一个独特的新课程，旨在确保 对计算科学和以疾病为导向的生理学都有基本的理解，在此之前 学习计算方法的实用技能，这些方法直接应用于导师提供的数据 研究经验。该项目的参与者包括研究生、博士后研究员、 生物医学工程师、住院医师和临床研究员被广泛地从现有的 教育、培训和研究计划，通过国际声誉和生产力 高度投入的参与教职员工。该计划利用机构资源进行计划 管理和稳健的计划评估，以保持适应和响应需求 参与者。该计划的短期目标是：1)提供基础知识 生理学和计算科学；2)提供使用、创造和传播的实用技能 以及3)提供研究环境，以丰富技能磨练和 生产力。该计划的长期目标是：4)扩大对 影响糖尿病、消化和肾脏疾病研究的计算分析；以及5) 吸引和留住影响糖尿病、消化和肾脏疾病领域的不同科学家- 以研究为导向。通过完成该计划，我们预计这些科学家将形成一座桥梁 在理解人类健康的生理和计算方法之间往往相距遥远 并形成了影响糖尿病、消化和肾脏领域的一代不同的科学家 疾病。

Project Summary / Abstract Modern biomedical science and medicine, with large varied and complex datasets, requires a paradigm shift in our educational models to train the next generation of scientists and physicians capable of performing and interpreting computational analyses. Current educational models have created a critical gap of expertise between computational data scientists and disease-oriented physiologists. The Specific Aim of this proposal is to establish an innovative educational model to promote the training of computational skills for immediate and direct application to research experiences and create the next generation of biomedical scientists to lead new discoveries in diabetes, digestive and kidney disease-oriented research. The Mayo Clinic Research Education Program in Computational Autonomic Neurobiology is a unique new program designed to ensure foundational understanding of both computational science and disease-oriented physiology, prior to learning practical skills in computational methods that are directly applied to data from mentored research experiences. Participants in the program, including graduate students, post-doctoral fellows, biomedical engineers, medical residents, and clinical fellows, are recruited widely from existing educational, training and research programs via the international reputations and productivity of the highly invested participating faculty. The program leverages institutional resources for program administration and robust program evaluation to remain adaptive and responsive to the needs of participants. The short-term objectives of the program are to: 1) provide foundational knowledge in physiology and computational science; 2) provide practical skill in the use creation and dissemination of computational workflows; and 3) provide a research environment to enrich skill honing and productivity. The long-term objectives of the program are to: 4) expand the use and access of computational analyses to impact diabetes, digestive and kidney disease-oriented research; and 5) attract and retain diverse scientists that impact the fields of diabetes, digestive and kidney disease- oriented research. By completing the program, we anticipate these scientists will form a bridge between the often distant physiological and computational approaches to understand human health and form a generation of diverse scientists that impact the fields of diabetes, digestive and kidney diseases.