GRK 1772: Computational Systems Biology

GRK 1772：计算系统生物学

• 批准号: 191312833
• 金额: --
• 依托单位: Max-Planck-Institut für molekulare Genetik (MPIMG)
• 依托单位国家: 德国
• 项目类别: Research Training Groups
• 财政年份: 2011
• 资助国家: 德国
• 起止时间: 2010-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/191312833?language=en
• 关键词: GRK; 1772; Computational; Systems; Biology

Biology has turned into a quantitative, information-driven science. Like physics in the first half of the twentieth century, biology now generates very challenging questions and masses of data that drive the development of theory and technology. There are numerous applications of biological research results in medicine and healthcare, biotechnology, and environmental sciences. Thus, there is an urgent need for highly educated researchers who are familiar with molecular and cellular biology and who possess at the same time a rich repertoire of mathematical concepts and methods, understanding of information theory and informatics as well as physics and chemistry. While these fields of knowledge are traditionally taught separately, systems biology requires researchers who can combine such skills. Our Research Training Group for Computational Systems Biology (CSB) is embedded in the Berlin research environment with healthcare and clinical research, biotechnology and basic biological research, as well as many strong theoretical groups (e.g. the mathematical research center Matheon). In this renewal proposal we refined the very successful research program of the first funding period, for example we apply theoretical methods that have been developed during the last period to specific biological problems. We slightly adjusted the focus of the research program, by including more projects that combine theoretical and experimental work, in particular by integrating early-stage researchers. The overarching theme is to understand general regulatory principles in biological systems. Our research topics will be grouped into four pillars: (a) reverse engineering of biological networks, (b) understanding cellular variability, (c) unraveling adaptation mechanisms in biological networks, and (d) understanding regulation mechanisms mediated by RNA molecules and their interactions. The qualification concepts of CSB comprise (i) inspiring and challenging research projects for the early-stage scientists embedded in the research program of CSB, (ii) individual supervision and mentoring, (iii) advanced education in concepts and methods of computational systems biology through lectures and practical courses as well as soft skills training, and (iv) early involvement in the research community. We support gender equality of the members of this graduate school with various structural as well as individual measures.

生物学已经成为一门定量的、信息驱动的科学。就像世纪上半叶的物理学一样，生物学现在产生了非常具有挑战性的问题和大量的数据，这些数据推动了理论和技术的发展。生物研究成果在医学和医疗保健、生物技术和环境科学中有许多应用。因此，迫切需要受过高等教育的研究人员，他们熟悉分子和细胞生物学，同时拥有丰富的数学概念和方法，了解信息论和信息学以及物理和化学。虽然这些领域的知识传统上是分开教授的，但系统生物学需要能够将这些技能联合收割机结合起来的研究人员。我们的计算系统生物学研究培训小组（CSB）嵌入在柏林的研究环境中，包括医疗保健和临床研究，生物技术和基础生物学研究，以及许多强大的理论小组（例如数学研究中心Matheon）。在这个更新提案中，我们改进了第一个资助期非常成功的研究计划，例如，我们将上一个时期开发的理论方法应用于特定的生物学问题。我们稍微调整了研究计划的重点，包括更多的项目，结合联合收割机的理论和实验工作，特别是通过整合早期研究人员。总体主题是了解生物系统中的一般调控原则。我们的研究主题将分为四个支柱：（a）生物网络的逆向工程，（B）了解细胞的变异性，（c）解开生物网络中的适应机制，（d）了解RNA分子及其相互作用介导的调节机制。 CSB的资格概念包括（i）为嵌入CSB研究计划的早期科学家提供鼓舞人心和具有挑战性的研究项目，（ii）个人监督和指导，（iii）通过讲座和实践课程以及软技能培训，在计算系统生物学的概念和方法方面进行高级教育，以及（iv）早期参与研究社区。我们通过各种结构和个人措施支持该研究生院成员的性别平等。