The BioRECIPE Knowledge Representation Format.

IF 3.7 2区生物学 Q1 BIOCHEMICAL RESEARCH METHODS ACS Synthetic Biology Pub Date : 2024-08-16 Epub Date: 2024-07-25 DOI:10.1021/acssynbio.4c00096

Emilee Holtzapple, Gaoxiang Zhou, Haomiao Luo, Difei Tang, Niloofar Arazkhani, Casey Hansen, Cheryl A Telmer, Natasa Miskov-Zivanov

引用次数: 0

Abstract

The BioRECIPE (Biological system Representation for Evaluation, Curation, Interoperability, Preserving, and Execution) knowledge representation format was introduced to standardize and facilitate human-machine interaction while creating, verifying, evaluating, curating, and expanding executable models of intra- and intercellular signaling. This format allows a human user to easily preview and modify any model component, while it is at the same time readable by machines and can be processed by a suite of model development and analysis tools. The BioRECIPE format is compatible with multiple representation formats, natural language processing tools, modeling tools, and databases that are used by the systems and synthetic biology communities.

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BioRECIPE 知识表示格式。

BioRECIPE （用于评估、整理、互操作性、保存和执行的生物系统表征）知识表征格式的引入是为了在创建、验证、评估、整理和扩展细胞内和细胞间信号传递的可执行模型时实现标准化并促进人机交互。这种格式允许人类用户轻松预览和修改任何模型组件，同时它也可被机器读取，并可由一套模型开发和分析工具进行处理。BioRECIPE 格式兼容多种表示格式、自然语言处理工具、建模工具以及系统和合成生物学界使用的数据库。

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来源期刊

ACS Synthetic Biology 生物-

CiteScore

8.00

自引率

10.60%

发文量

380

审稿时长

6-12 weeks

期刊介绍： The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.