Integrative Dynamic Omics Profiling: A First Step Towards Personalized Medicine

综合动态组学分析：迈向个性化医疗的第一步

• 批准号: 8829693
• 负责人: George Ioannou Mias
• 金额: $ 24.85万
• 依托单位: MICHIGAN STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-15 至 2017-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8829693
• 关键词: Accounting; Address; Adopted; Algorithms; Award; B-Lymphocytes; Biological; Biological Models; Biological Process; Caring; Categories; Cell Line; Cells; Collection; Communities; Complex; Computing Methodologies; Data; Development; Diagnosis; Disease; Excision; Faculty; Funding; Gene Proteins; Genetic; Genomics; Individual; Investigation; Laboratories; Lead; Learning; Measures; Medical; Mentors; Metabolic Pathway; Methodology; Methods; Modeling; Molecular; Monitor; NF-kappa B; Nature; Noise; Onset of illness; Outcome; Pathway interactions; Patients; Phase; Physiological; Positioning Attribute; Precursor B-Lymphoblast; Preventive Medicine; Procedures; Process; Proteomics; Research; Resources; Sampling; Signal Pathway; Statistical Methods; System; Techniques; Technology; Testing; Time; Transcript; base; biological systems; career; computerized data processing; design; dynamical evolution; human disease; improved; innovation; insight; interest; lymphoblast; metabolomics; network models; new technology; novel; personalized medicine; programs; protein metabolite; research study; response; tool; treatment effect

The rapid advancement in available -omics technologies is expected to greatly aid the development and application of personalized, precise and preventive medicine. In particular, novel medical insights are expected through the integration of genomic information through the global monitoring of changes in molecular components, such as trancriptomic, proteomic and metabolomic information in conjunction with monitoring varying physiological states. This necessitates the development of new methodology and tools to handle the analysis and integration of multiple omic data with a view towards medical applicability. The proposed research of this 4-year K99/R00 proposal will begin at the laboratory of Dr. Michael Snyder, a renowned expert in genetics and multiple omics, who will act as the mentor for Dr. George Mias throughout the K99 year of the award. Foremost in this proposal is the development of a framework to integrate dynamic data obtained from monitoring multible omic information over multiple time points. The innovative methodology involves the development of statistical tools to analyze different omics technologies, including raw data processing, combining the individual omic data, categorizing the data in medically relevant categories, and ascertaining biological significance through pathway analyses. Considerations such as uneven sampling of data, lack of replicates and noise, inherent in obtaining samples from patients will be addressed during the K99 period. Additionally, the interactions between multiple omics components will be inferred through changes in expression, and time-varying networks will be defined that can be analyzed for detail explanation of transitions between physiological states. In order to develop the computational methodology, highly precise experiments will be performed, by monitoring gene, protein and metabolite expression over multiple time points in stimulated B-cells[lymphoblasts in K99 period and primary B cells in R00 period], with focus on the important and complex Nuclear Factor kappa B (NF¿B) signaling pathways. Furthermore, developed tools, algorithms and data will be disseminated to the scientific community in the R00 period. The proposed learning activities of the K99/R00 award will allow Dr. Mias to adapt his research approaches to omics integration across multiple platforms, and acquire the necessary experimental background for independent investigations. The unique nature of Dr. Snyder¿s lab, will provide Dr. Mias the opportunity to closely interact and collaborate with experimental experts conducting research at the forefront of omics research in genetics. Moreover, the lab¿s extensive resources readily available to Dr. Mias will greatly facilitate his research and academic endeavors. The K99/R00 award will enable Dr. Mias to to smoothly transition into an independent faculty position in the R00 phase and successfully lead novel investigations in his own laboratory.

可用的组学技术的快速发展预计将大大有助于发展和 个性化、精准化和预防性医疗的应用。特别是，新的医学见解有望 通过整合基因组信息，通过全球监测分子水平的变化， 成分，如转录组学、蛋白质组学和代谢组学信息， 不同的生理状态这就需要开发新的方法和工具来处理 分析和整合多个omic数据，以实现医疗适用性。拟议研究 这个为期4年的K99/R 00提案的开始将在迈克尔斯奈德博士的实验室，一个著名的专家， 遗传学和多组学，谁将作为导师博士乔治米亚斯整个K99年的 奖该提案的首要内容是开发一个框架，以整合从以下方面获得的动态数据： 在多个时间点监测多个组学信息。创新的方法包括 开发统计工具，分析不同的组学技术，包括原始数据处理， 组合个体组学数据，将数据分类为医学相关类别，并确定 生物学意义通过路径分析。考虑因素，如数据抽样不均匀，缺乏 将在K99期间解决从患者中获取样本时固有的重复和噪音问题。 此外，多个组学组分之间的相互作用将通过以下变化来推断： 表达式和时变网络将被定义，可以分析这些网络以详细解释转换 生理状态之间的区别为了发展计算方法，高精度的实验 将通过监测多个时间点的基因、蛋白质和代谢物表达来进行， 刺激的B细胞[K99期的淋巴母细胞和R 00期的原代B细胞]，重点关注重要的 和复杂的核因子κ B（NF B）信号通路。此外，开发的工具，算法 并将在R 00期间向科学界传播数据。拟议的学习活动 K99/R 00奖将使Mias博士能够调整他的研究方法， 平台，并获得独立调查所需的实验背景。独特的 斯奈德博士实验室的性质，将为米亚斯博士提供密切互动和合作的机会， 在遗传学组学研究的前沿进行研究的实验专家。此外，实验室 米亚斯博士可随时获得的广泛资源将极大地促进他的研究和学术努力。 K99/R 00奖将使Mias博士能够顺利过渡到独立的教师职位， R 00阶段，并在自己的实验室成功地领导了新的研究。