权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Biostatistics Training for Basic Biomedical Research

基础生物医学研究的生物统计学培训

基本信息

批准号：
8290439
负责人：
Viswanathan Ramakrishnan
金额：
$ 5.13万
依托单位：
MEDICAL UNIVERSITY OF SOUTH CAROLINA
依托单位国家：
美国
项目类别：
财政年份：
2005
资助国家：
美国
起止时间：
2005-07-01 至 2014-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8290439
关键词：
Biomedical Research Biometry Training

项目摘要

DESCRIPTION (provided by applicant): The sequencing of the human genome has set the stage for the next major frontier in biology, the proteome, paving the way for the new "omics" era in biomedical research. The exploding cascade of data requires integration of bioinformatics tools for data representation and manipulation, and sophisticated statistical and mathematical approaches for validating, analyzing, modeling and, finally, unifying and interpreting the myriad of "omics" data to infer biological function. The Biostatistics Training for Basic Biomedical Research (BTBBR) predoctoral program at the Medical University of South Carolina (MUSC) trains biostatisticians and bioinformaticians to assume key roles in this new generation of basic biomedical research. The BTBBR program integrates rigorous training in biostatistical theory and methods with bioinformatics to address quantitative frontiers in modern multi-disciplinary biological research. To enhance cross-fertilization of disciplinary themes, facilitate collaboration and team mentoring, enrich research opportunities for the students, and improve efficiency and effectiveness of predoctoral training at the interface of the quantitative and biological sciences, this renewal application will Integrate two predoctoral training programs at MUSC that that currently share faculty and complementary foci (in bioinformatics and biostatistical applications for the neurosciences) with the BTBBR. The BTBBR program capitalizes on an established, successful college- wide program offering a common basic science curriculum that provides structured, broad-based didactic and laboratory training in the basic biomedical sciences for entering graduate students; an established biostatistics program that emphasizes integration of biological knowledge and biostatistical principles; an established bioinformatics program with faculty embedded in basic science departments; and a robust atmosphere of collaboration among biostatistical and basic biomedical science researchers. The BTBBR program focuses the biomedical science training component in five biomedical research areas in which MUSC has nationally recognized strengths: proteomics and biomarkers, cell signaling, lipidomics, neurobiology, and biolmaging and bioengineering. RELEVANCE (See instructions): This predoctoral research training program will prepare the next generation of biomedical investigators who will be experts in quantitative, computational and systems science approaches in order to accelerate the pace of translating knowledge discovered in the laboratory into new screening, diagnostic and treatment tools that can be individualized to improve the health of people dealing with major diseases such as cancer, diabetes, heart disease, Alzheimer's and Parkinson's disease.

描述(申请人提供)：人类基因组测序为生物学的下一个主要前沿--蛋白质组奠定了基础，为生物医学研究的新“组学”时代铺平了道路。数据的爆炸性级联需要集成生物信息学工具来表示和处理数据，以及复杂的统计和数学方法来验证、分析、建模，最后统一和解释无数的“组学”数据，以推断生物功能。南卡罗来纳医科大学(MUSC)的基础生物医学研究生物统计学培训(BTBBR)博士前课程培养生物统计学家和生物信息学家，以在这一新一代基础生物医学研究中发挥关键作用。BTBBR计划将生物统计学理论和方法的严格培训与生物信息学相结合，以解决现代多学科生物学研究中的定量前沿问题。为了加强学科主题的交叉培养，促进合作和团队指导，丰富学生的研究机会，并提高定量和生物科学相结合的博士前培训的效率和效果，此次续签申请将整合MUSC的两个博士前培训项目，这两个项目目前与BTBBR共享教员和互补重点(生物信息学和神经科学的生物统计应用)。BTBBR计划利用了一个成熟的、成功的大学范围的计划，该计划提供了一个共同的基础科学课程，为进入研究生提供有组织的、广泛的基础生物医学科学的教学和实验室培训；一个已经建立的生物统计学计划，强调生物知识和生物统计学原理的整合；一个已经建立的生物信息学计划，其教员嵌入在基础科学系中；以及生物统计和基础生物医学科学研究人员之间良好的合作氛围。BTBBR计划将生物医学科学培训部分集中在MUSC具有国家认可优势的五个生物医学研究领域：蛋白质组学和生物标记物、细胞信号、脂质组学、神经生物学以及生物成像和生物工程。相关性(参见说明)：该博士前研究培训计划将培养下一代生物医学研究人员，他们将成为定量、计算和系统科学方法方面的专家，以加快将实验室发现的知识转化为新的筛查、诊断和治疗工具的步伐，这些工具可以个性化，以改善与癌症、糖尿病、心脏病、阿尔茨海默氏症和帕金森氏症等重大疾病打交道的人的健康。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Estimating Gompertz Growth Curves from Marine Mammal Strandings in the Presence of Missing Data.

在存在缺失数据的情况下估计海洋哺乳动物搁浅的 Gompertz 生长曲线。

DOI：
发表时间：
2010
期刊：
International journal of ecological economics and statistics
影响因子：
0.3
作者：
Shotwell,Mary;McFee,Wayne;Slate,ElizabethH
通讯作者：
Slate,ElizabethH

Network modeling reveals steps in angiotensin peptide processing.

网络建模揭示了血管紧张素肽加工的步骤。

DOI：
10.1161/hypertensionaha.111.00318
发表时间：
2013
期刊：
Hypertension (Dallas, Tex. : 1979)
影响因子：
0
作者：
Schwacke,JohnH;Spainhour,JohnChristianG;Ierardi,JessalynL;Chaves,JoseM;Arthur,JohnM;Janech,MichaelG;Velez,JuanCarlosQ
通讯作者：
Velez,JuanCarlosQ

A Bayesian mixture model for missing data in marine mammal growth analysis.