Mathematical & Algorithmic Analysis of Natural and Artificial DNA Sequences

数学

• 批准号: 0218568
• 负责人: Bhubaneswar Mishra
• 金额: $ 30万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-15 至 2005-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0218568&HistoricalAwards=false
• 关键词: Mathematical; & Algorithmic; Analysis; Natural

EIA-218568Bhubaneswar MishraNew York UniversityMathematical and Algorithmic Analysis of Natural and Artificial DNA SequencesThe PI is developing tools that play an important role in understanding the properties of both natural and artificial genomes and thus, elucidates how such DNA evolves under natural and artificial conditions (in vitro or in vivo). The ultimate applications range from building error-resilient biological computers all the way up to understanding how genome structures (e.g., genes, gene families, synteny groups, haplotype blocks, chromosomes, etc.) have naturally evolved.With this goal in mind, the PI is developing several modeling and statistical algorithms with efficient implementations in order to solve design problems in genomics, biosensors, biocomputation and evolutionary biology. The final "tool box'' design contains: a software environment and language that allows users to visualize and analyze long DNA or RNA molecules, a "gene grammar" to model various genome-wide evolutionary processes, statistical analysis of the structures of various natural genomic DNAs evolving under replication and proof-reading processes and finally, a physical annotation of the genome that can be used in designing genomic microarrays or aptamers for biosensors.

自然和人工DNA序列的数学和算法分析PI正在开发工具，在理解自然和人工基因组的特性方面发挥重要作用，从而阐明这些DNA在自然和人工条件下（体外或体内）是如何进化的。最终的应用范围从构建抗错误的生物计算机一直到理解基因组结构（例如，基因、基因家族、共群、单倍型块、染色体等）如何自然进化。为了实现这一目标，PI正在开发几种有效实现的建模和统计算法，以解决基因组学，生物传感器，生物计算和进化生物学中的设计问题。最终的“工具箱”设计包含：允许用户可视化和分析长DNA或RNA分子的软件环境和语言，用于模拟各种全基因组进化过程的“基因语法”，用于在复制和校对过程中进化的各种天然基因组DNA结构的统计分析，以及可用于设计基因组微阵列或生物传感器适体的基因组物理注释。