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
基本信息
- 批准号:1262603
- 负责人:
- 金额:$ 55.12万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-07-01 至 2017-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
High-throughput sequencing has been producing millions of protein sequences without solved structures and functional annotations, which raise demand for computational tools especially user-friendly web servers for protein structure and functional elucidation. This project will transform RaptorX, a popular protein structure modeling web server, to one that can also annotate functions of a protein sequence and the quality of a theoretical protein model in the absence of the corresponding native structure. The resultant new server will greatly facilitate the interpretation and proper usage of a theoretical protein model, just like what E-value does for homology search. The server will also predict functions of a protein sequence with coverage beyond what can be reached by native-structure-based methods and accuracy much higher than sequence-based methods. Ultimately, the project will deliver a long-term sustainable cyber-infrastructure for protein sequence, structure and functional analysis that enables transformative biological and biomedical research. This project will also advance protein structure and functional prediction by developing several sophisticated computational methods for model quality assessment and functional prediction. Proteins play fundamental roles in all biological processes. Complete description of protein structures and functions is a fundamental step towards understanding biological life. This project will benefit a broad range of biological/biomedical applications, such as the study of plant metabolic pathways, drug design, and bio-energy development. The research results will be communicated to the broader community through a variety of venues (wiki, talks, papers and posters). The software will be freely available to the public. Since its first release in August 2011, RaptorX has processed dozens of thousands of protein modeling and analysis jobs for more than 3500 users around the world. After the new RaptorX is implemented, it will contribute much more to the broader community. This project will also contribute to computer science by studying machine learning problems inspired from protein bioinformatics. This project shall enrich and disseminate knowledge on protein bioinformatics, machine learning and web programming. It will also train minority students, future K-12 science teachers and nationwide students in the Illinois online bioinformatics program. All involved students will receive training in the intersection of computer science, molecular biology, biophysics, and biochemistry. The research results will be integrated into course materials, which will be used in the classes and also freely available to the public.
高通量测序已经产生了数百万个蛋白质序列,但没有解决结构和功能注释,这增加了对计算工具的需求,特别是用于蛋白质结构和功能阐明的用户友好的网络服务器。该项目将把 RaptorX(一种流行的蛋白质结构建模网络服务器)转变为在缺乏相应天然结构的情况下也可以注释蛋白质序列的功能和理论蛋白质模型的质量的服务器。由此产生的新服务器将极大地促进理论蛋白质模型的解释和正确使用,就像 E-value 对同源搜索所做的那样。服务器还将预测蛋白质序列的功能,其覆盖范围超出基于天然结构的方法所能达到的范围,并且准确性比基于序列的方法高得多。最终,该项目将为蛋白质序列、结构和功能分析提供长期可持续的网络基础设施,从而实现变革性的生物学和生物医学研究。该项目还将通过开发几种用于模型质量评估和功能预测的复杂计算方法来推进蛋白质结构和功能预测。蛋白质在所有生物过程中发挥着基础作用。对蛋白质结构和功能的完整描述是理解生物生命的基本一步。该项目将有利于广泛的生物/生物医学应用,例如植物代谢途径的研究、药物设计和生物能源开发。研究结果将通过各种场所(维基、演讲、论文和海报)传达给更广泛的社区。该软件将免费向公众开放。自 2011 年 8 月首次发布以来,RaptorX 已为全球 3500 多名用户处理了数十万个蛋白质建模和分析作业。新的 RaptorX 实施后,将为更广泛的社区做出更多贡献。该项目还将通过研究受蛋白质生物信息学启发的机器学习问题,为计算机科学做出贡献。该项目将丰富和传播蛋白质生物信息学、机器学习和网络编程方面的知识。它还将为伊利诺伊州在线生物信息学项目的少数族裔学生、未来的 K-12 科学教师和全国学生提供培训。所有参与的学生都将接受计算机科学、分子生物学、生物物理学和生物化学交叉领域的培训。研究成果将被纳入课程材料中,在课堂上使用,并免费向公众开放。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(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
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Huimei Liao;Siyuan Leng;Junhai Yang;Jinbo Xu;Junhao Zhang;Jinling Tang - 通讯作者:
Jinling Tang
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:
$ 55.12万 - 项目类别:
Standard Grant
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
- 批准号:
1564955 - 财政年份:2016
- 资助金额:
$ 55.12万 - 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:
$ 55.12万 - 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:
$ 55.12万 - 项目类别:
Standard Grant
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