Workshop: Biocomplexity VII - Unraveling the Function and Kinetics of Biochemical Networks: From Experiments to Systems Biology, at Indiana University-Bloomington May 9-12, 2005

即使生物体的完整基因组序列是可用的，只有少数基因组分的功能和相互作用是清楚的。目前，未表征蛋白质的功能通常是基于序列相似性、共同结构基序、基因顺序、基因融合事件或基因表达相似性来推断的。 最近，新的数学和计算方法已被引入基于基因在网络中的作用的功能预测。 这些方法使我们能够独立于结构或序列的同源性对蛋白质进行功能预测，并提供了一种方法来表征尚未使用高通量技术的已发表生物数据进行研究的蛋白质。 该提案要求为生物复杂性研究所和印第安纳州大学信息学院组织的“生物复杂性七：揭开生物化学网络的功能和动力学：从实验到系统生物学”讲习班提供部分资金。 生物复杂性第七期研讨会旨在汇集各种方法的专家，通过开发适合于分析高通量数据集的数学和计算方法，了解他们如何能够联合收割机来阐明基因和蛋白质在网络环境中的功能。研讨会的目标是：（一）探索和介绍新的实验和理论方法的发展，以重建复杂的生物化学网络; ㈡促进工程师、物理学家、数学家、生物学家和化学家之间的互动，他们对重建复杂的生物化学网络的各个方面感兴趣，及（iii）为初级教员及研究生提供一个与多方面专家交流的平台。研讨会的科学重点将是1）讨论和开发工具，以重建遗传和生物化学途径的结构和动力学，2）使这些方法的应用复杂化的主要数学和计算问题，以及3）来自数学、物理、化学的最佳当前解决方案和现有解决方案，工程和计算机科学，可以应用于解决问题1）。 该研讨会将汇集许多学科的研究人员，包括数学，实验和理论生物学，物理学，工程学和计算机科学。更广泛的影响：该研讨会将促进遗传和生物化学网络动力学的实验和理论研究的合作和发展，并使广泛的外部研究人员接触网络重建和功能的问题。 该研讨会是专门组织提供高级研究人员，初级教师和研究生之间的互动。 海报会议将促进这种互动。 会议记录将汇编成册，分发给所有与会者，发表在一份期刊特刊上，并将通过万维网以电子方式提供。 我们将讨论的方法将适用于任何生物体，包括人类，其中只有3%到5%的基因功能是已知的。 随着我们更好地了解基因和蛋白质在网络环境中的功能，我们可以更好地预测和控制它们对内部和外部扰动的反应。

Even when full genomic sequences for an organism are available, the functions and interactions of only a small number of gene components are clear. Presently, the functions of uncharacterized proteins have usually been inferred on the basis of sequence similarities, common structural motifs, gene order, gene fusion events, or similarities in gene expression. Recently, new mathematical and computational methods have been introduced for functional predictions based on the role of genes in networks. These methods allow us to perform functional predictions for proteins independent of homologies in structure or sequence and provide a way to characterize proteins that have not yet been studied using published biological data from high-throughput technologies. This proposal requests partial funding for the workshop "Biocomplexity VII: Unraveling the Function and Kinetics of Biochemical Networks: From Experiments to Systems Biology," organized by the Biocomplexity Institute and the School of Informatics at Indiana University. The Biocomplexity VII workshop aims to bring together specialists in a broad array of methodologies to see how they can combine to explicate the functions of genes and proteins in a network context by developing mathematical and computational approaches suited for the analysis of high-throughput data sets. The objectives of the workshop are to: (i) To explore and present the development of new experimental and theoretical approaches for the purposes of reconstructing complex biochemical networks; (ii) To promote interaction between engineers, physicists, mathematicians, biologists, and chemists with interests in all aspects of reconstructing complex biochemical networks, and (iii) To provide a forum for junior faculty and graduate students to interact with a wide range of experts.Intellectual merit: The scientific focus of the workshop will be on 1) discussing and developing tools to reconstruct the structure and kinetics of genetic and biochemical pathways, 2) the main mathematical and computational issues which complicate applications of such methods and 3) the best current solutions and existing solutions from mathematics, physics, chemistry, engineering and computer sciences which can be applied to solve the problems in 1). The Workshop will bring together researchers in many disciplines, including mathematics, experimental and theoretical biology, physics, engineering, and computer science.Broader impact: This workshop will promote collaboration and development of both experimental and theoretical studies of genetic and biochemical network dynamics and to expose a broad range of outside researchers to problems in network reconstruction and function. The Workshop is organized specifically to provide interactions between senior researchers, junior faculty, and graduate students. The poster session will facilitate such interaction. Proceedings of the conference will be compiled and disseminated to all participants, published in a journal special issue and will be made available electronically over the world-wide-web. The methodologies we will be discussing will be applicable to any organism, including humans, where only three to five percent of gene function is known. As we better understand the functions of genes and proteins in a network context, we can better predict and control their responses to internal and external perturbations.