CytoCopasi:化学系统生物学目标和药物发现可视化数据分析平台

IF 4.4 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Hikmet Emre Kaya, Kevin J Naidoo
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引用次数: 0

摘要

动机 针对机制复杂的疾病进行目标发现和药物评估,需要一个简化的化学系统分析平台。目前可用的工具缺乏对反应动力学的重视、对相关数据库的访问以及在化学尺度上可视化扰动的算法,无法提供定量细节和简化的可视化数据分析功能。结果 CytoCopasi 是一个基于 Maven 的 Cytoscape 应用程序,它将 COPASI 的化学系统分析功能与 Cytoscape 及其插件应用程序的可视化和数据库访问工具相结合。介绍了 CytoCopasi 的多种功能,包括自证模型构建、通过路径和参数数据库 KEGG 和 BRENDA 构建模型。通过对癌症 RAF/MEK/ERK 通路的药物能力研究,说明了比较系统生物学可视化分析工具集。可用性 COPASI 文件、模拟数据、原生库和手册可在 https://github.com/scientificomputing/CytoCopasi 上获取 补充信息 补充数据可在 Bioinformatics online 上获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CytoCopasi: A Chemical Systems Biology Target and Drug Discovery Visual Data Analytics Platform
Motivation Target discovery and drug evaluation for diseases with complex mechanisms call for a streamlined chemical systems analysis platform. Currently available tools lack the emphasis on reaction kinetics, access to relevant databases, and algorithms to visualize perturbations on a chemical scale providing quantitative details as well streamlined visual data analytics functionality. Results CytoCopasi, a Maven-based application for Cytoscape that combines the chemical systems analysis features of COPASI with the visualization and database access tools of Cytoscape and its plugin applications has been developed. The diverse functionality of CytoCopasi through ab initio model construction, model construction via pathway and parameter databases KEGG and BRENDA is presented. The comparative systems biology visualization analysis toolset is illustrated through a drug competence study on the cancerous RAF/MEK/ERK pathway. Availability The COPASI files, simulation data, native libraries, and the manual are available on https://github.com/scientificomputing/CytoCopasi Supplementary information Supplementary data is available at Bioinformatics online.
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来源期刊
Bioinformatics
Bioinformatics 生物-生化研究方法
CiteScore
11.20
自引率
5.20%
发文量
753
审稿时长
2.1 months
期刊介绍: The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.
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