ABI Development: Developing RaptorX Web Portal for Protein Structure and Functional Study

ABI 开发:开发用于蛋白质结构和功能研究的 RaptorX 门户网站

基本信息

  • 批准号:
    1564955
  • 负责人:
  • 金额:
    $ 55.7万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-07-15 至 2020-06-30
  • 项目状态:
    已结题

项目摘要

Proteins play fundamental roles in all biological processes. Complete description of protein structures and functions is a fundamental step towards understanding biological life and has various applications. Millions of protein sequences are available, but a majority of them have no experimentally-solved structures and functions. This project aims to greatly improve RaptorX, a fully-automated web server for computational prediction of protein structure and function, with the goal to deliver a long-term sustainable web portal to facilitate transformative research in biology. This web portal shall benefit a broad range of biological and biomedical applications, such as genome annotation, understanding of disease processes, drug design, precision medicine and even biomaterial and bio-energy development. The results will be disseminated to the broader community through a variety of venues: web servers, standalone software, publications and talks. Since late in 2011, RaptorX has served 25,000 worldwide users including middle- and high-school students. The standalone programs have been downloaded by 1500 worldwide users. After this project is fulfilled, RaptorX will contribute much more to the broader community. Students involved in this project will receive training in the intersection of computer science, molecular biology, biophysics, and biochemistry. Undergraduate and underrepresented students will be recruited through summer intern programs and collaborators. The research results will be integrated into course materials and used in the Illinois online bioinformatics program. The RaptorX web server was originally developed for only template-based protein modeling. This project will transform RaptorX by first developing a few novel and powerful deep learning (e.g., Deep Conditional Convolutional Neural Fields) and structure learning (e.g., group graphical lasso) methods to significantly improve the accuracy of protein structure and functional prediction and then conducting an efficient implementation. The resultant RaptorX will be able to perform much more accurate prediction of protein secondary and tertiary structure, solvent accessibility and disordered regions, and the quality of a theoretical protein 3D model (in the absence of natives). This project will also expand the RaptorX server to perform contact prediction and contact-assisted protein folding for proteins without good templates. The RaptorX web server is available at http://raptorx.uchicago.edu, from which users can also download the standalone programs.
蛋白质在所有生物过程中起着重要作用。蛋白质结构和功能的完整描述是理解生物生命的基本步骤,并具有各种应用。数以百万计的蛋白质序列是可用的,但其中大多数没有实验解决的结构和功能。该项目旨在大大改进RaptorX,这是一个用于蛋白质结构和功能计算预测的全自动Web服务器,其目标是提供一个长期可持续的门户网站,以促进生物学的变革性研究。这个门户网站将有利于广泛的生物和生物医学应用,如基因组注释,疾病过程的理解,药物设计,精确医学,甚至生物材料和生物能源的开发。结果将通过各种渠道传播给更广泛的社区:网络服务器、独立软件、出版物和讲座。自2011年底以来,RaptorX已为全球25,000名用户提供服务,其中包括初中和高中学生。这些独立程序已被全球1500名用户下载。在这个项目完成后,RaptorX将为更广泛的社区做出更多贡献。参与这个项目的学生将接受计算机科学、分子生物学、生物物理学和生物化学交叉领域的培训。本科生和代表性不足的学生将通过暑期实习生计划和合作者招募。研究结果将被整合到课程材料中,并用于伊利诺伊州在线生物信息学计划。RaptorX Web服务器最初仅用于基于模板的蛋白质建模。该项目将通过首先开发一些新颖而强大的深度学习来改变RaptorX(例如,深度条件卷积神经场)和结构学习(例如,群图lasso)方法,显著提高蛋白质结构和功能预测的准确性,进而进行高效的实现。由此产生的RaptorX将能够更准确地预测蛋白质的二级和三级结构、溶剂可及性和无序区域,以及理论蛋白质3D模型的质量(在没有本地人的情况下)。该项目还将扩展RaptorX服务器,以针对没有良好模板的蛋白质进行接触预测和接触辅助蛋白质折叠。RaptorX网络服务器可在http://raptorx.uchicago.edu上找到,用户也可以从那里下载独立程序。

项目成果

期刊论文数量(0)
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Jinbo Xu其他文献

iTreePack: Protein Complex Side-Chain Packing by Dual Decomposition
iTreePack:通过双重分解进行蛋白质复合侧链包装
  • DOI:
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jian Peng;R. Hosur;B. Berger;Jinbo Xu
  • 通讯作者:
    Jinbo Xu
De Novo Protein Structure Prediction by Big Data and Deep Learning
通过大数据和深度学习进行从头蛋白质结构预测
  • DOI:
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sheng Wang;Jinbo Xu
  • 通讯作者:
    Jinbo Xu
A Robust and Efficient Risk Assessment Framework for Multi-Step Attacks
针对多步攻击的稳健且高效的风险评估框架
1 Supplement : iWRAP : An interface threading approach for protein-protein interaction prediction
1 补充:iWRAP:一种用于蛋白质-蛋白质相互作用预测的界面线程方法
  • DOI:
  • 发表时间:
    2010
  • 期刊:
  • 影响因子:
    0
  • 作者:
    R. Hosur;Jinbo Xu;J. Bienkowska;B. Berger
  • 通讯作者:
    B. Berger
Rapid and Accurate Protein Side Chain Prediction Using Local Backbone Information Only
仅使用本地主干信息快速准确地预测蛋白质侧链
  • DOI:
  • 发表时间:
    2007
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jing Zhang;Xin Gao;Jinbo Xu;Ming Li
  • 通讯作者:
    Ming Li

Jinbo Xu的其他文献

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{{ truncateString('Jinbo Xu', 18)}}的其他基金

AF:III: small: Convex optimization for protein-protein interaction network alignment
AF:III: 小:蛋白质-蛋白质相互作用网络对齐的凸优化
  • 批准号:
    1618648
  • 财政年份:
    2016
  • 资助金额:
    $ 55.7万
  • 项目类别:
    Standard Grant
ABI Development: Continued Development of RaptorX Server for Protein Structure and Functional Prediction
ABI 开发:持续开发用于蛋白质结构和功能预测的 RaptorX 服务器
  • 批准号:
    1262603
  • 财政年份:
    2013
  • 资助金额:
    $ 55.7万
  • 项目类别:
    Standard Grant
CAREER: Exact and Approximate Algorithms for 3D Structure Modeling of Protein-Protein Interactions
职业:蛋白质-蛋白质相互作用 3D 结构建模的精确和近似算法
  • 批准号:
    1149811
  • 财政年份:
    2012
  • 资助金额:
    $ 55.7万
  • 项目类别:
    Continuing Grant
Algorithm and Web Server for Low-homology Protein Threading
低同源性蛋白质线程的算法和网络服务器
  • 批准号:
    0960390
  • 财政年份:
    2010
  • 资助金额:
    $ 55.7万
  • 项目类别:
    Standard Grant

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