Biomedical Informatics Training Program

生物医学信息学培训计划

基本信息

批准号：
7457663
负责人：
Pierre Baldi
金额：
$ 88.41万
依托单位：
UNIVERSITY OF CALIFORNIA-IRVINE
依托单位国家：
美国
项目类别：
财政年份：
2002
资助国家：
美国
起止时间：
2002-07-01 至 2012-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7457663
关键词：
Achievement Address Admission activity Adopted Advertising Advisory Committees Algorithms Analysis of Variance Appointment Architecture Area Arts Award Awareness Back Belief Biochemical Biochemistry Bioinformatics Biological Biological Neural Networks Biological Phenomena Biological Sciences Biology Biomedical Engineering Biophysics Cell Cycle Cell physiology Cells Cellular Structures Cellular biology Characteristics Chemicals Class Classification Collaborations Communities Complex Computational Biology Computational Science Computer software Computers Computing Methodologies Consultations Contracts DNA Daily Data Data Analyses Data Reporting Database Management Systems Databases Development Developmental Cell Biology Dimensions Discipline Disease Disease regression Doctor of Philosophy Ear Ecology Educational Curriculum Educational process of instructing Electronic Mail Embryology Engineering Enrollment Environment Enzyme Kinetics Equation Esapent Evaluation Evaluation Studies Event Evolution Experimental Designs Face Faculty Feedback Fertilization Figs - dietary Fostering Funding GTP-Binding Proteins Gene Expression Gene Expression Regulation Generations Genetic Genetic Programming Genetic Transcription Genets Genome Genomics Goals Grant Growth Health Health Promotion Home environment Human Imagery Individual Industry Informatics Infrastructure Activities Inservice Training Institutes Institution Interdisciplinary Study International Internet Interview Java Journals Kinetics Knowledge Laboratories Laboratory Research Language Lead Learning Letters Life Ligands Machine Learning Markov Chains Mathematics Medical Medical Computer Science Medicine Mentors Metabolic Pathway Methodology Methods Mining Modeling Molecular Molecular Biology Molecular Genetics Morphogenesis NIH Grants and Contracts Names Nature Neural Network Simulation Nonlinear Dynamics Numbers Occupations Outcome Pamphlets Pattern Formation Performance Phosphotransferases Physics Positioning Attribute Postdoctoral Fellow Principal Investigator Probability Procedures Process Program Evaluation Programming Languages Progress Reports Proteins Proteomics Publications Purpose Pythons Qualifying Range Recording of previous events Records Recruitment Activity Reporting Research Research Activity Research Personnel Research Project Grants Research Training Resources Rotation Schools Science Scientist Score Second Messenger Systems Security Sequence Analysis Signal Transduction Signal Transduction Pathway Silicon Site Societies Software Tools Solutions Statistical Models Structure Students Surveys System Systems Biology Techniques Thermodynamics Time Today Training Training Programs Translations Travel United States National Institutes of Health Universities Virus Visit Work Workload abstracting analytical method base biomedical informatics biophysical chemistry career catalyst cohesion computer science computerized tools concept data structure day design design and construction enzyme mechanism expectation experience falls feeding high throughput technology informatics training interdisciplinary collaboration interest lectures macromolecule markov model mathematical model medical schools member physical science posters pre-doctoral professor programs protein protein interaction protein structure prediction receptor research study response scientific computing second messenger simulation size skills social software development statistics success symposium theories tool

项目摘要

DESCRIPTION (provided by applicant): Genomic and other high throughput technologies in the biomedical sciences are generating overwhelming amounts of data that must be processed, analyzed, and interpreted. These massive amounts of data have created a critical need for theoretical, algorithmic, software, and hardware advances in storing, retrieving, networking, processing, modeling, visualizing, and interpreting biological and medical information. These needs continue to inspire new concepts in computer science, such as genetic algorithms, neural networks, computer viruses, and DMA computing methods. Because of these developments, computer science applications in the fields of biology and medicine showcase the latest advances in core computer science from hardware to software, from algorithms to databases, and from theory to user interfaces. This cross fertilization has enriched both fields and will continue to do so in the coming decades. To continue to meet these challenges, the UCI Biomedical Informatics Training (BIT) Program trains graduate students and postdoctoral fellows at the interface of the life and computational sciences for professional careers in bioinformatics and computational biology. The BIT Program, administered by the UCI Institute for Genomics and Bioinformatics, integrates a first year Mathematical and Computational Biology Gateway Program with biomedical informatics training programs in the UCI Schools of Biological and Physical Sciences, Engineering, Medicine, and Information and Computer Sciences. This Program emphasizes interdisciplinary teamwork using a dual mentor approach involving interdisciplinary thesis research projects. Required core courses in mathematics, statistics, and computer science provide students with the computational tools required to address complex biological questions. Regular faculty/trainee meetings, quarterly reviews, and an annual mini-symposium of student projects stimulate interaction, inform faculty of progress, and foster group cohesion as well as interdisciplinary exchange of information among trainees. In summary, the BIT Program is producing a critically-needed generation of world class scholars who will develop new bionformatics and computational biology tools to solve fundamental problems in biology and medicine for the improvement of human health.

描述（由申请人提供）：生物医学科学中的基因组和其他高通量技术正在产生大量的数据，这些数据必须处理，分析和解释。这些大量数据在存储，检索，网络，处理，建模，可视化和解释生物学和医学信息方面对理论，算法，软件和硬件的进步产生了迫切需求。这些需求继续激发计算机科学中的新概念，例如遗传算法，神经网络，计算机病毒和DMA计算方法。由于这些发展，生物学和医学领域的计算机科学应用程序展示了从硬件到软件的核心计算机科学的最新进展，从算法到数据库，以及从理论到用户界面。这种交叉施肥已经丰富了这两个领域，并将在未来几十年中继续这样做。为了继续应对这些挑战，UCI生物医学信息学培训（BIT）计划火车研究生和博士后研究员在生活和计算科学的界面生物信息学和计算生物学的职业。由UCI基因组学和生物信息学研究所管理的BIT计划将第一年的数学和计算生物学网关计划与UCI生物学和物理科学，工程，医学，医学以及信息和计算机科学的生物医学信息学培训计划相结合。该计划使用涉及跨学科论文研究项目的双重指导方法强调跨学科的团队合作。数学，统计和计算机科学领域所需的核心课程为学生提供了解决复杂生物学问题所需的计算工具。定期的教师/学员会议，季度评论和年度小型学生项目刺激互动，促进进步教师以及寄养小组的凝聚力以及学员之间的信息跨学科交流。总而言之，该BIT计划正在生产急需的世界一流学者，他们将开发新的生物形式和计算生物学工具，以解决生物学和医学中的基本问题，以改善人类健康。