Cell Illustrator 4.0:系统生物学的计算平台。

Q2 Medicine In Silico Biology Pub Date : 2010-01-01 DOI:10.3233/ISB-2010-0415
Masao Nagasaki, Ayumu Saito, Euna Jeong, Chen Li, Kaname Kojima, Emi Ikeda, Satoru Miyano
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引用次数: 98

摘要

Cell Illustrator是一个系统生物学的软件平台,它使用Petri网的概念来建模和模拟生物途径。它是为在实验室工作的生物科学家设计的。最新版本的Cell Illustrator 4.0使用Java Web Start技术,并增强了新的功能,包括:使用本体信息的自动图形网格布局算法;使用细胞系统标记语言(CSML) 3.0和细胞系统本体3.0工具;参数搜索模块;高性能仿真模块;CSML数据库管理系统;从CSML模型到编程语言(FORTRAN, C, c++, Java, Python和Perl)的转换;从SBML、CellML和BioPAX导入;导出为SVG和HTML。Cell Illustrator采用面向对象风格的混合Petri网扩展,因此生物通路模型可以包括诸如DNA序列,分子密度,3D定位信息,带帧移位的转录,带密码子表的翻译以及生化反应等对象。
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Cell Illustrator 4.0: a computational platform for systems biology.

Cell Illustrator is a software platform for Systems Biology that uses the concept of Petri net for modeling and simulating biopathways. It is intended for biological scientists working at bench. The latest version of Cell Illustrator 4.0 uses Java Web Start technology and is enhanced with new capabilities, including: automatic graph grid layout algorithms using ontology information; tools using Cell System Markup Language (CSML) 3.0 and Cell System Ontology 3.0; parameter search module; high-performance simulation module; CSML database management system; conversion from CSML model to programming languages (FORTRAN, C, C++, Java, Python and Perl); import from SBML, CellML, and BioPAX; and, export to SVG and HTML. Cell Illustrator employs an extension of hybrid Petri net in an object-oriented style so that biopathway models can include objects such as DNA sequence, molecular density, 3D localization information, transcription with frame-shift, translation with codon table, as well as biochemical reactions.

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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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