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Linking Text Mining and Data Mining for Biomedical Knowledge Discovery

连接文本挖掘和数据挖掘以发现生物医学知识

基本信息

批准号：
7886453
负责人：
CATHY H. WU
金额：
$ 15万
依托单位：
UNIVERSITY OF DELAWARE
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-08-19 至 2013-08-18
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7886453
关键词：
Adopted Architecture Benchmarking Bioinformatics Biological Biology Biomedical Research Communities Complex Computer software Controlled Vocabulary Data Data Display Data Quality Databases Development Diagnostic Disease Education and Outreach Educational workshop Environment Evaluation Future Gene Proteins Generations Genes Genome Goals Health Human Imagery Informatics Information Networks Information Resources Knowledge Knowledge Extraction Link Literature Maps Methods Metric Mining Molecular Names Online Systems Ontology Organism Pathway interactions Post-Translational Protein Processing Process Proteins Proteome PubMed Research Infrastructure Research Personnel Resources Semantics Services Signal Pathway Standardization Surveys System Systems Biology Systems Integration Training Translating base comparative data integration data mining digital disease diagnosis driving force gene function knowledge base open source outreach protein protein interaction text searching therapeutic target tool usability web interface

项目摘要

DESCRIPTION (provided by applicant): Systems integration is becoming the driving force for the 21st century biology. Researchers are systematically tackling gene functions and complex regulatory processes by studying organisms at different levels of organization, from genomes, transcriptomes and proteomes to metabolomes and interactomes. To fully realize the value of such high-throughput data requires advanced bioinformatics for integration, mining, comparative analysis, and functional interpretation. Furthermore, with an ever-increasing volume of biomedical literature now available electronically, there is both a pressing need and a great opportunity to fully utilize text mining tools for knowledge extraction. However, despite recent advancements, text mining tools are not being broadly used by biologists. Such a gap is partly due to the lack of close interactions between the text mining and the biological user communities. The goal of this application is to develop a digital research infrastructure that links text mining with data mining in the systems biology context for biomedical knowledge discovery, with a special focus on the utility and usability of the system for real world scientific applications. Building upon the bioinformatics framework we have already developed, as well as our close interactions with the biomedical research community, the specific aims are to: (i) integrate existing text mining tools to identify and extract protein and network information from scientific literature, (ii) connect text mining and data mining with omics data integration and web interface to capture and visualize network knowledge, and (iii) conduct user studies, develop scientific use cases, provide training and outreach, and disseminate the system to the broad biomedical user community. The digital information resource proposed herein will serve as an enabling environment for biomedical researchers to decipher knowledge from a plethora of information available in the literature and public databases, gaining a better understanding of biological and disease processes as a key to the basic understanding of human health and disease.

描述（由申请人提供）：