HIGH THROUGHPUT LITERATURE CURATION OF GENETIC REGULATION IN BACTERIAL MODELS

细菌模型中遗传调控的高通量文献整理

• 批准号: 9193091
• 负责人: Julio Collado-Vides
• 金额: $ 39.62万
• 依托单位: CENTER FOR GENOMIC SCIENCES
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9193091
• 关键词: Area; Bacteria; Bacterial Model; Binding Sites; Biological; Biological Process; Biology; Biomedical Research; Cells; Classification; Collection; Communities; Complex; Data Set; Databases; Effectiveness; Elements; Escherichia coli; Evolution; Foundations; Future; Gene Expression Regulation; Genes; Genetic; Genetic Programming; Genetic Transcription; Genome; Genomics; Growth; Human; International; Joints; Knowledge; Letters; Linguistics; Literature; Manuals; Methodology; Methods; Modeling; Molecular; Natural Language Processing; Nature; Ontology; Operon; Organism; Paper; Physiological; Physiological Processes; Planet Earth; Process; Property; Publications; Publishing; Reaction; Reading; Regulation; Regulon; Reporting; Research Infrastructure; Series; Signal Transduction; Site; Solid; Source; System; Technology; Text; Training; Transcription Initiation; Transcriptional Regulation; base; cell behavior; digital; electronic book; experience; feeding; functional genomics; improved; innovation; member; microbial community; model organisms databases; novel; novel strategies; promoter; prototype; public health relevance; response; software development; text searching; tool; transcription factor; usability

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.

描述（由申请人提供）：本提案的目的是实现一种新的方法来处理和访问包含在细菌模型中转录起始调节的科学出版物集合中的大量详细知识。原则上，这种处理和读取信息和新知识的模型适用于其他生物领域，可能使生物医学知识的任何领域受益。当然，制定新的战略来应对基因组学和生物医学研究中不断增长的知识是至关重要的。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，最终包括细胞的生理特性。我们将首先实现必要的技术，通过一个具有文本挖掘能力的计算系统来改进我们的策展，该系统可以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对论文进行预处理。由策展人选择的预先标记选项将加快他们的决策。句子和知识之间的累积精确映射将为文本挖掘技术提供训练集，以提高文本的自动提取。策展人实践将