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英文摘要
Project Summary/Abstract The DNA sequence of the human genome informs us as to the composition of proteins that make up healthy cells, but also altered compositions that create diseased cells. How protein production is controlled through the regulation of the genes that encode them is of critical importance for healthy and diseased cells. Knowing precisely where gene regulatory proteins bind, and are organized throughout the genome, including their interactions with each other, informs us as to how genes are regulated and mis-regulated. Since there are potentially thousands of different kinds of regulatory proteins and thousands of different kinds of human cell types and environmental responses that are a product of various subsets of regulatory proteins, the entire “universe” of gene regulatory events is quite substantial and consequently, quite costly to identify. One of the main bottlenecks in analysis of genomic data is efficient and scalable visualization approaches. The PEGR open source platform will provide programmatic access to any number of human cell sequenced datasets, from any stage of NGS processing, with the pipeline analysis results available for high-throughput machine learning testing and development. This project will empower discovery through the automated analysis and visualization of results from both small- and large-scale datasets. This architecture will include the following features: 1) a secure, cloud-based, metadata management system that instills best practices of experimental rigor, reproducibility, and data sharing; 2) automated Galaxy-based epigenomic data processing pipelines that provide easy-to-use “wizards” for standardized processing of common epigenomic data types; and 3) an easily de-ployable, open source software package as a means to disseminate data, tools, and discoveries via cloud services.
期刊论文(8)
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会议论文
DOI: 10.1101/gr.275472.121
发表时间: 2021-09
期刊: Genome research
影响因子: 7
作者: [Lai WKM, Mariani L, Rothschild G, Smith ER, Venters BJ, Blanda TR, Kuntala PK, Bocklund K, Mairose J, Dweikat SN, Mistretta K, Rossi MJ, James D, Anderson JT, Phanor SK, Zhang W, Zhao Z, Shah AP, Novitzky K, McAnarney E, Keogh MC, Shilatifard A, Basu U, Bulyk ML, Pugh BF]
通讯作者: Pugh BF
DOI: 10.1145/3311790.3396621
发表时间: 2020-07
期刊: PEARC20 : Practice and Experience in Advanced Research Computing 2020 : Catch the wave : July 27-31, 2020, Portland, Or Virtual Conference. Practice and Experience in Advanced Research Computing (Conference) (2020 : Online)
影响因子: --
作者: []
通讯作者:
DOI: 10.1371/journal.pcbi.1009859
发表时间: 2022-03
期刊: PLoS computational biology
影响因子: 4.3
作者: [Sun Q, Nematbakhsh A, Kuntala PK, Kellogg G, Pugh BF, Lai WKM]
通讯作者: Lai WKM
DOI: 10.1093/nar/gkaa618
发表时间: 2020-11-18
期刊: Nucleic acids research
影响因子: 14.9
作者: [Yamada N, Rossi MJ, Farrell N, Pugh BF, Mahony S]
通讯作者: Mahony S
共 7 条
    Understanding the predeterminants of transcription factor regulatory activity
    • 批准号:
      10798541
    • 项目类别:
    • 资助金额:
      $11.37万
    • 财政年份:
      2022
    • 负责人:
      Shaun Aengus Mahony
    • 依托单位:
    Understanding the predeterminants of transcription factor regulatory activity
    • 批准号:
      10544796
    • 项目类别:
    • 资助金额:
      $45.53万
    • 财政年份:
      2022
    • 负责人:
      Shaun Aengus Mahony
    • 依托单位:
    Understanding the predeterminants of transcription factor regulatory activity
    • 批准号:
      10330514
    • 项目类别:
    • 资助金额:
      $45.56万
    • 财政年份:
      2022
    • 负责人:
      Shaun Aengus Mahony
    • 依托单位:
    Genome-wide structural organization of proteins within human gene regulatory complexes
    • 批准号:
      10078275
    • 项目类别:
    • 资助金额:
      $45.31万
    • 财政年份:
      2018
    • 负责人:
      Shaun Aengus Mahony
    • 依托单位:
    海外基金