Biomedical Big Data Training Grant

 描述（由申请人提供）：这个基础广泛的T32提案的重点是支持在加州大学洛杉矶分校从事生物医学大数据分析研究的研究生。在过去几年里，人们越来越认识到，生物医学科学正在经历一场变革，这是由新技术的发展所主导的，这些技术极大地提高了生成数据的能力。其中包括DNA和RNA测序技术;使用质谱法测量蛋白质和代谢物丰度;以及用于筛选和表型分析的多种其他高通量平台。再加上医学成像和电子病历的进步，数据量的增长速度比以往任何时候都快。虽然加州大学洛杉矶分校还有其他几个培训赠款，但没有一个专门针对分析和关联大型生物医学数据集的一般问题。因此，我们在这里提出的这个新的培训补助金填补了一个关键的利基，这将使我们能够支持研究生在生物医学“大数据”分析的基本方面。这一努力实现了一套定制的大数据分析课程的新颖开发，沿着了专业的团队建设活动，包括BI数据挑战和大数据中心的校外实习。该培训计划将为我们的学生在大数据科学的未来发展定位，促进加州大学洛杉矶分校这一关键领域的发展。我们认为，该计划将是我们的生物信息学计划和大数据生物医学科学在加州大学洛杉矶分校的增长至关重要。支持该培训计划的教师代表了来自UCLA校园的跨学科研究人员，包括工程与应用科学学院;生命科学学院和医学院。许多教师都是国家认可的学科领导者;集体，这些人提供了一套全面和互补的（资助）研究领域和技能，丰富了培训经验。

 DESCRIPTION (provided by applicant): This broad-based T32 proposal is focused on supporting graduate students pursuing Biomedical Big Data Analysis research at UCLA. Over the past few years there has been increasing recognition that the biomedical sciences are undergoing a transformation, led by the development of new technologies that have enormously increased the capacity to generate data. These include technologies to sequence DNA and RNA; measure protein and metabolite abundances using mass spectrometry; as well as multiple other high throughput platforms for screening and phenotyping. Coupled with the advances in medical imaging and EHRs, the amount of data is growing faster than ever before. While several other training grants exist at UCLA, none are specifically focused on the general problem of analyzing and relating large biomedical data sets. Thus this new training grant we propose here fills a critical niche that will allow us to support graduate students in fundamental aspects of biomedical "big data" analysis. This effort realizes the novel development of a tailored set of courses in big data analysis, along with specialized team building activities in bi data challenges and extramural internships in big data centers. This training program will position our students for the future growth in big data science, fostering the growth of this critial area at UCLA. We posit that this program will be critical for the growth of our bioinformatics program and big data biomedical science at UCLA. Faculty supporting this training program represent an interdisciplinary group of researchers from across the UCLA campus, including the Schools of Engineering & Applied Sciences; College of Life Sciences and the Medical School. Many of the faculty are nationally recognized leaders in their disciplines; collectively, these individuals provide a comprehensive and complementary set of (funded) research areas and skills that enrich the training experience.