Identification of Biological Materials of Unknown Origin

来源不明的生物材料的鉴定

• 批准号: 7168805
• 负责人: Khalid Sayood
• 金额: $ 14.95万
• 依托单位: UNIVERSITY OF NEBRASKA LINCOLN
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-02-01 至 2011-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7168805
• 关键词: Address; Algorithms; Antibiotic Resistance; Area; Automation; Award; Bacillus anthracis; Bacteria; Bacterial DNA; Base Sequence; Behavior; Bioinformatics; Biological; Biological Models; Biological Process; Biological Testing; Bioterrorism; Brucella abortus; Burkholderia mallei; Burkholderia pseudomallei; Characteristics; Classification; Cluster Analysis; Commit; Communicable Diseases; Computational Biology; Coxiella; DNA; DNA Sequence; Data; Detection; Development; Discrimination; Doctor of Medicine; Doctor of Philosophy; Escherichia coli; Frequencies; Funding; Genes; Genome; Genomics; Goals; Image; Individual; Institution; Intervention; Investigation; Knowledge; Laboratories; Lead; Mediating; Medical; Mentors; Methods; Microbiology; Modeling; Nebraska; Oligonucleotides; Organism; Outcome; Pathogenicity; Pattern; Personal Satisfaction; Phylogenetic Analysis; Play; Polynucleotides; Procedures; Promoter Regions; Public Health; Research; Research Personnel; Research Training; Role; Salmonella enterica; Shigella flexneri; Site; Speech; Staging; Staphylococcus aureus; Stretching; Structure; Study Section; Techniques; Testing; Therapeutic Intervention; Time; Training; Training Activity; Training Programs; Trees; United States National Institutes of Health; Universities; Wood material; Work; base; biosecurity; career; cost; desire; expectation; experience; hazard; information organization; innovation; interest; mathematical model; microbial; organizational structure; programs; tool; virology

DESCRIPTION (provided by applicant): The applicant's long term goal is to understand and elucidate structure and organization within DNA sequences and uncover their relationship to biological functions. The objective of this application, which is a step toward the attainment of this long term goal, is to develop techniques for elucidating occult structural features in bacterial DNA which can be used for identification and differentiation of microbial organisms, including organisms whose genome has not been completely sequenced, using short fragments of DNA. A parallel goal is to achieve investigative independence as a computational biologist. The latter goal will be accomplished through coursework and training in the laboratories of Steven Hinrichs, M.D. The urgent need for rapid identification tests for biological materials has intensified because of the threat posed by bioterrorism. Rapid identification of both the fact and the mode of attack is essential for timely therapeutic intervention. The ability to identify bacteria based on short sequences of incomplete or possibly corrupt sequences allows for hazard detection, automation, and low cost distributed sensing capability. The identification techniques will be developed using three tools: the average mutual information (AMI) profile which reflects statistical relationships between bases along the DNA sequence, a cluster analysis technique developed by the applicant and co-workers which identifies genome specific trinucleotide clustering patterns, and a parsing technique for identification of polynucleotide sequences of interest. Components of the AMI profile which possess discriminatory capabilities will be identified by decomposing the profile and analyzing the coefficients using both supervised and unsupervised classification. The clustering strategy will be refined by correlating parameters in the technique with known biological behavior. Signature trinucleotide and polynucleotide clustering patterns will be identified for organisms of interest. The different classifications will be combined into a tree structured test for a model panel of bacteria of medical interest.

描述（由申请人提供）：申请人的长期目标是理解和阐明 DNA 序列内的结构和组织，并揭示它们与生物功能的关系。该应用的目的是实现这一长期目标的一步，是开发阐明细菌 DNA 中隐秘结构特征的技术，该技术可用于使用短 DNA 片段识别和区分微生物，包括基因组尚未完全测序的生物。一个并行的目标是实现作为计算生物学家的研究独立性。后一个目标将通过医学博士 Steven Hinrichs 实验室的课程作业和培训来实现。由于生物恐怖主义造成的威胁，对生物材料快速识别测试的迫切需求已经加剧。快速识别事实和攻击方式对于及时治疗干预至关重要。基于不完整或可能损坏序列的短序列识别细菌的能力允许危险检测、自动化和低成本分布式传感能力。识别技术将使用三种工具开发：平均互信息（AMI）图谱，反映DNA序列上碱基之间的统计关系，由申请人和同事开发的聚类分析技术，用于识别基因组特异性三核苷酸聚类模式，以及用于识别感兴趣的多核苷酸序列的解析技术。 AMI 档案中具有区分能力的组成部分将通过分解档案并使用监督和无监督分类分析系数来识别。将通过将技术中的参数与已知的生物行为相关联来完善聚类策略。将鉴定感兴趣的生物体的特征三核苷酸和多核苷酸聚类模式。不同的分类将被组合成树形结构测试，用于医学感兴趣的细菌模型组。