TranSyT, an innovative framework for identifying transport systems.

IF 4.4 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Bioinformatics Pub Date : 2023-08-01 DOI:10.1093/bioinformatics/btad466

Emanuel Cunha, Davide Lagoa, José P Faria, Filipe Liu, Christopher S Henry, Oscar Dias

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引用次数: 0

Abstract

Motivation: The importance and rate of development of genome-scale metabolic models have been growing for the last few years, increasing the demand for software solutions that automate several steps of this process. However, since TRIAGE's release, software development for the automatic integration of transport reactions into models has stalled.

Results: Here, we present the Transport Systems Tracker (TranSyT). Unlike other transport systems annotation software, TranSyT does not rely on manual curation to expand its internal database, which is derived from highly curated records retrieved from the Transporters Classification Database and complemented with information from other data sources. TranSyT compiles information regarding transporter families and proteins, and derives reactions into its internal database, making it available for rapid annotation of complete genomes. All transport reactions have GPR associations and can be exported with identifiers from four different metabolite databases. TranSyT is currently available as a plugin for merlin v4.0 and an app for KBase.

Availability and implementation: TranSyT web service: https://transyt.bio.di.uminho.pt/; GitHub for the tool: https://github.com/BioSystemsUM/transyt; GitHub with examples and instructions to run TranSyT: https://github.com/ecunha1996/transyt_paper.

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transsyt，一个识别运输系统的创新框架。

动机:在过去几年中，基因组尺度代谢模型的重要性和发展速度一直在增长，增加了对自动化该过程几个步骤的软件解决方案的需求。然而，自从TRIAGE发布以来，将运输反应自动集成到模型中的软件开发已经停滞不前。结果:在这里，我们提出了运输系统跟踪器(TranSyT)。与其他运输系统注释软件不同，TranSyT不依赖于人工管理来扩展其内部数据库，该数据库来源于从运输商分类数据库检索的高度管理的记录，并辅以其他数据源的信息。TranSyT编译有关转运蛋白家族和蛋白质的信息，并将反应导出到其内部数据库中，使其可用于快速注释完整基因组。所有转运反应都与GPR相关，并可与来自四个不同代谢物数据库的标识符一起导出。TranSyT目前作为merlin v4.0的插件和KBase的应用程序可用。可用性和实现:TranSyT web服务:https://transyt.bio.di.uminho.pt/;该工具的GitHub: https://github.com/BioSystemsUM/transyt;GitHub的例子和指令运行TranSyT: https://github.com/ecunha1996/transyt_paper。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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.