HIGH THROUGHPUT LITERATURE CURATION OF GENETIC REGULATION IN BACTERIAL MODELS

描述（由申请人提供）：本提案的目的是实施一种处理和访问科学出版物集合中包含的关于细菌模型中转录起始调控的大量详细知识的新方法。原则上，这种处理和阅读信息和新知识的模式适用于其他生物学领域，可能有益于生物医学知识的任何领域。当然，制定新的战略来应对基因组学和整个生物医学研究中产生的不断增加的知识量是至关重要的。提高传统的高质量人工管理科学出版物的效率，也将使我们能够扩展生物学知识的类型，超越机制及其在基因组中的元素，开始包括它们与更大的调节过程的联系，并最终包括细胞的生理特性。我们将首先实施必要的技术，通过具有文本挖掘功能的计算系统来改进我们的策展，以便在人类专家策展人识别哪些句子包含要添加到数据库中的信息之前预处理论文。策展人选择的预先标记的选项将加速他们的决定。句子和精选知识之间的累积精确映射将为文本挖掘技术提供训练集，以提高其自动提取。策展人将 变得更有效率，使我们能够精选高影响力的已发表评论，将机制置于其生理过程和一般生物学的丰富背景中。我们的建议的另一个相关组成部分是通过生物学中的新概念来改进调节过程的建模，这些新概念捕获了更大的共调节基因及其串联反应的集合。从当地监管机构的所有互动开始，共同监管的监管机构 它们的作用域将被纳入构建复杂决策的生物砖，因为它们被编码在基因组中。这些概念容器捕捉知识的组织来描述细胞能力的遗传编程。这些建议将在一个国际联盟内正式提出，该联盟的重点是丰富基因调控的标准模型或本体论，供科学界使用。最后，将建立一个门户网站，用于浏览大量（5 000多份）相关论文的所有句子。不同的导航途径将主要使用两种技术，一种是从原始句子自动生成简单句子作为输入，另一种是基于主题或本体对论文进行分类。他们的结合将使一个新的导航阅读系统。如果我们实现了我们的目标，这个项目将提供一个原理验证原型，具有明显的创新性，更高水平的大量综合知识。未来的发展方向可能会使这些概念和方法适用于包括人类在内的高等生物的生物学。

DESCRIPTION (provided by applicant): The aim of this proposal is to implement a novel way of processing and accessing the vast detailed knowledge contained within collections of scientific publications on the regulation of transcription initiation in bacterial models. In princple, this model for processing and reading information and new knowledge is applicable to other biological domains, potentially benefiting any area of biomedical knowledge. It is certainly criticl to generate new strategies to cope with the ever-increasing amount of knowledge generated in genomics and in biomedical research at large. Improving the efficiency of the traditional high-quality manual curation of scientific publications will enable us also to expand the type of biological knowledge, beyond mechanisms and their elements in the genome, to start including their connections with larger regulated processes and eventually physiological properties of the cell. We will first implement the necessary technology to improve our curation by means of a computational system that has text mining capabilities for preprocessing the papers before a human expert curator identifies which sentences contain the information that is to be added to the database. Premarked options selected by the curators will accelerate their decisions. The accumulative precise mapping between sentences and curated knowledge will provide training sets for text mining technologies to improve their automatic extraction. The curator practices will become more efficient, enabling us to curate selected high-impact published reviews to place mechanisms into a rich context of their physiological processes and general biology. Another relevant component of our proposal is the improved modeling of regulated processes by means of new concepts in biology that capture larger collections of coregulated genes and their concatenated reactions. Starting from all interactions of a local regulator, coregulated regulators and their domain of action will be incorporated to construct the biobricks of complex decisions, as they are encoded in the genome. These are conceptual containers that capture the organization of knowledge to describe the genetic programming of cellular capabilities. These proposals will be formalized and proposed within an international consortium focused in enriching standard models or ontologies of gene regulation for use by the scientific community. Finally, a portal to navigate across all the sentences of a given corpus of a large number (more than 5,000) of related papers will be implemented. The different avenues of navigation will essentially use two technologies, one dealing with automatically generating simpler sentences from original sentences as input, and the other one with the classification of papers based on their theme or ontology. Their combination will enable a novel navigation reading system. If we achieve our aims, this project will give a proof-of-principle prototype with clearly innovative higher levels of large amounts of integrated knowledge. Future directions may adapt these concepts and methods to the biology of higher organisms, including humans.