Sivakumar Tadi Venkata, Giri Varun, Park Jin Hwan, Kim Tae Yong, Bhaduri Anirban
Bioinformatics Lab, Samsung Advanced Institute of Technology, Bangalore 560037, India.
Biomaterials Lab, Materials Center, Samsung Advanced Institute of Technology, Gyeonggi-Do 443803, Korea.
Bioinformatics. 2016 Nov 15;32(22):3522-3524. doi: 10.1093/bioinformatics/btw491. Epub 2016 Aug 2.
Biochemical pathways engineering is often used to synthesize or degrade target chemicals. In silico screening of the biochemical transformation space allows predicting feasible reactions, constituting these pathways. Current enabling tools are customized to predict reactions based on pre-defined biochemical transformations or reaction rule sets. Reaction rule sets are usually curated manually and tailored to specific applications. They are not exhaustive. In addition, current systems are incapable of regulating and refining data with an aim to tune specificity and sensitivity. A robust and flexible tool that allows automated reaction rule set creation along with regulated pathway prediction and analyses is a need. ReactPRED aims to address the same.
ReactPRED is an open source flexible and customizable tool enabling users to predict biochemical reactions and pathways. The tool allows automated reaction rule creation from a user defined reaction set. Additionally, reaction rule degree and rule tolerance features allow refinement of predicted data. It is available as a flexible graphical user interface and a console application.
ReactPRED is available at: https://sourceforge.net/projects/reactpred/ CONTACT: anirban.b@samsung.com or ty76.kim@samsung.comSupplementary information: Supplementary data are available at Bioinformatics online.
生化途径工程常用于合成或降解目标化学品。对生化转化空间进行计算机筛选能够预测构成这些途径的可行反应。当前的支持工具是根据预定义的生化转化或反应规则集定制的,用于预测反应。反应规则集通常是手动策划的,并且针对特定应用进行定制,并不详尽。此外,当前的系统无法对数据进行调节和优化,以调整特异性和敏感性。因此,需要一个强大且灵活的工具,能够自动创建反应规则集,并进行受调控的途径预测和分析。ReactPRED旨在解决这一问题。
ReactPRED是一个开源的、灵活且可定制的工具,可让用户预测生化反应和途径。该工具允许根据用户定义的反应集自动创建反应规则。此外,反应规则度和规则容差功能可对预测数据进行优化。它以灵活的图形用户界面和控制台应用程序的形式提供。
ReactPRED可在以下网址获取:https://sourceforge.net/projects/reactpred/ 联系方式:anirban.b@samsung.com 或 ty76.kim@samsung.com 补充信息:补充数据可在《生物信息学》在线获取。