课题基金 / 基金详情

AF: Small: Algorithmic Techniques for High-throughput Analysis of Long Reads

AF: Small: Algorithmic Techniques for High-throughput Analysis of Long Reads
AF:小:长读长高通量分析的算法技术
批准号:
1816027
负责人:
Srinivas Aluru
金额:
$42.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-10-01 至 2022-09-30

项目摘要

项目成果

Srinivas Aluru的其他基金

相似基金

相关文献

中文摘要
翻译
DNA测序领域已经从桑格测序(长度为700-1000个碱基对或bp)快速发展到短读段(100-200 bp)的大规模并行高通量测序,再到产生长读段(5,000 bp)和超长读段(50,000 bp)的最近进展。目前迫切需要开发有效的算法来分析长读数据集的背景下,他们使无数的生物应用。长读技术维持高错误率,但具有更有吸引力的错误分布特性,通常允许对结果质量的概率保证。该项目将导致在开发用于长读序的生物信息学算法方面的基础研究进展,沿着可分发的开源软件产品,以促进生命科学界立即采用这些软件产品。该项目旨在通过设计可证明有效的算法、对结果质量进行正式表征、开发可扩展到更大数据集的方法以及对长读序测序持续发展所带来的变化具有鲁棒性的方法,来推进长读序测序的映射、组装和生物应用。所解决的问题包括(i)超长读段到参考基因组的分裂读段映射,(ii)基于布隆过滤器的数据结构的开发以实现空间优化和完美的统计灵敏度,(iii)用于将长读段映射到由基于紧凑图的结构表示的参考基因组的集合的算法,(iv)用于划分长读段以促进二倍体组装中的单倍型的鉴定的算法,以及(v)用于基因组对基因组比较的长读启发的无比对算法,以及由这些实现的重要生物学应用。该研究将强调利用真实的数据集,与实际遇到的问题和应用的相关性,以及合作者和其他专家的独立验证。该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。
英文摘要
The field of DNA sequencing has rapidly evolved from Sanger sequencing (700-1000 base pairs, or bp, in length) to massively parallel high-throughput sequencing of short reads (100-200 bp) to the more recent advances in generating long ( 5,000 bp) and ultra-long ( 50,000 bp) reads. There is currently an urgent need to develop efficient algorithms for analyzing long-read datasets in the context of the myriad biological applications they enable. Long read technologies sustain high error rates but with more attractive error distribution characteristics that often permit probabilistic guarantees on the quality of results. This project will result in fundamental research advances in developing bioinformatics algorithms for long-read sequencing, along with distributable open-source software products to facilitate their immediate adoption by the life sciences community. The award will also support interdisciplinary training, and undergraduate participation in research.The project seeks to advance mapping, assembly, and biological applications of long-read sequencing through the design of provably efficient algorithms, formal characterization of the quality of results, development of methods that scale to larger datasets, and methods that are robust to changes brought about by continued developments in long read sequencing. Problems addressed include (i) split-read mapping of ultra-long reads to a reference genome, (ii) development of data structures based on bloom filters to achieve space optimization and perfect statistical sensitivity, (iii) algorithms for mapping long reads to a collection of reference genomes represented by compact graph-based structures, (iv) algorithms for partitioning long reads to facilitate identification of haplotypes in diploid assemblies, and (v) long-read inspired alignment free algorithms for genome-to-genome comparison, as well as important biological applications enabled by these. The research will emphasize utilization of real datasets, relevance to practically encountered problems and applications, and independent validation by collaborators and other experts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(14)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1093/bioinformatics/bty597
发表时间: 2018-09-01
期刊: BIOINFORMATICS
影响因子: 5.8
作者: [Jain, Chirag, Koren, Sergey, Aluru, Srinivas]
通讯作者: Aluru, Srinivas
DOI: 10.1089/cmb.2019.0066
发表时间: 2020-01-03
期刊: JOURNAL OF COMPUTATIONAL BIOLOGY
影响因子: 1.7
作者: [Jain, Chirag, Zhang, Haowen, Aluru, Srinivas]
通讯作者: Aluru, Srinivas
DOI: 10.1101/682799
发表时间: 2019-06
期刊: bioRxiv
影响因子: --
作者: [Chirag Jain;Haowen Zhang;A. Dilthey;S. Aluru]
通讯作者: Chirag Jain;Haowen Zhang;A. Dilthey;S. Aluru
DOI: 10.1089/cmb.2022.0266
发表时间: 2022-11-01
期刊: JOURNAL OF COMPUTATIONAL BIOLOGY
影响因子: 1.7
作者: [Jain, Chirag, Gibney, Daniel, Thankachan, Sharma V.]
通讯作者: Thankachan, Sharma V.
共 7 条
    A scalable integrated multi-modal single cell analysis framework for gene regulatory and cell-cell interaction networks
    • 批准号:
      2233887
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $54.58万
    • 财政年份:
      2023
    • 负责人:
      Srinivas Aluru
    • 依托单位:
    BD Hubs: Collaborative Proposal: SOUTH:The South Big Data Innovation Hub
    • 批准号:
      1916589
    • 项目类别:
      Cooperative Agreement
    • 资助金额:
      $203.16万
    • 财政年份:
      2019
    • 负责人:
      Srinivas Aluru
    • 依托单位:
    EAGER: A Framework for Learning Graph Algorithms with Applications to Social and Gene Networks
    • 批准号:
      1841351
    • 项目类别:
      Standard Grant
    • 资助金额:
      $30.0万
    • 财政年份:
      2018
    • 负责人:
      Srinivas Aluru
    • 依托单位:
    MRI: Acquisition of an HPC System for Data-Driven Discovery in Computational Astrophysics, Biology, Chemistry, and Materials Science
    • 批准号:
      1828187
    • 项目类别:
      Standard Grant
    • 资助金额:
      $369.93万
    • 财政年份:
      2018
    • 负责人:
      Srinivas Aluru
    • 依托单位:
    国内基金
    海外基金
    昼夜节律性small RNA在血斑形成时间推断中的法医学应用研究
    • 批准号:
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
    • 依托单位:
    tRNA-derived small RNA上调YBX1/CCL5通路参与硼替佐米诱导慢性疼痛的机制研究
    • 批准号:
    • 项目类别:
      省市级项目
    • 资助金额:
      10.0万元
    • 批准年份:
      2022
    • 负责人:
      张祥忠
    • 依托单位:
    Small RNA调控I-F型CRISPR-Cas适应性免疫性的应答及分子机制
    Small RNAs调控解淀粉芽胞杆菌FZB42生防功能的机制研究
    • 批准号:
      31972324
    • 项目类别:
      面上项目
    • 资助金额:
      58.0万元
    • 批准年份:
      2019
    • 负责人:
      高学文
    • 依托单位: