工具箱
计算机科学
眼镜蛇
SBML公司
生物信息学
系统生物学
脚本语言
标记语言
计算生物学
可用性
可视化
数据挖掘
程序设计语言
生物
XML
人机交互
操作系统
基因
生物化学
作者
Jan Schellenberger,Richard Que,Ronan M. T. Fleming,Ines Thiele,Jeffrey D. Orth,Adam M. Feist,Daniel C. Zielinski,Aarash Bordbar,Nathan E. Lewis,Sorena Rahmanian,Joseph Kang,Daniel R. Hyduke,Bernhard Ø. Palsson
出处
期刊:Nature Protocols
[Nature Portfolio]
日期:2011-08-04
卷期号:6 (9): 1290-1307
被引量:1910
标识
DOI:10.1038/nprot.2011.308
摘要
Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a substantial update of this in silico toolbox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include (i) network gap filling, (ii) 13C analysis, (iii) metabolic engineering, (iv) omics-guided analysis and (v) visualization. As with the first version, the COBRA Toolbox reads and writes systems biology markup language–formatted models. In version 2.0, we improved performance, usability and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the toolbox and validate results. This toolbox lowers the barrier of entry to use powerful COBRA methods.
科研通智能强力驱动
Strongly Powered by AbleSci AI