Stress Knowledge Map: A knowledge graph resource for systems biology analysis of plant stress responses.

IF 9.4 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Plant Communications Pub Date : 2024-06-10 Epub Date: 2024-04-15 DOI:10.1016/j.xplc.2024.100920
Carissa Bleker, Živa Ramšak, Andras Bittner, Vid Podpečan, Maja Zagorščak, Bernhard Wurzinger, Špela Baebler, Marko Petek, Maja Križnik, Annelotte van Dieren, Juliane Gruber, Leila Afjehi-Sadat, Wolfram Weckwerth, Anže Županič, Markus Teige, Ute C Vothknecht, Kristina Gruden
{"title":"Stress Knowledge Map: A knowledge graph resource for systems biology analysis of plant stress responses.","authors":"Carissa Bleker, Živa Ramšak, Andras Bittner, Vid Podpečan, Maja Zagorščak, Bernhard Wurzinger, Špela Baebler, Marko Petek, Maja Križnik, Annelotte van Dieren, Juliane Gruber, Leila Afjehi-Sadat, Wolfram Weckwerth, Anže Županič, Markus Teige, Ute C Vothknecht, Kristina Gruden","doi":"10.1016/j.xplc.2024.100920","DOIUrl":null,"url":null,"abstract":"<p><p>Stress Knowledge Map (SKM; https://skm.nib.si) is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical, signaling, and regulatory molecular interactions in plants: a highly curated model of plant stress signaling (PSS; 543 reactions) and a large comprehensive knowledge network (488 390 interactions). Both were constructed by domain experts through systematic curation of diverse literature and database resources. SKM provides a single entry point for investigations of plant stress response and related growth trade-offs, as well as interactive explorations of current knowledge. PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin. Here, we describe the features of SKM and show, through two case studies, how it can be used for complex analyses, including systematic hypothesis generation and design of validation experiments, or to gain new insights into experimental observations in plant biology.</p>","PeriodicalId":52373,"journal":{"name":"Plant Communications","volume":null,"pages":null},"PeriodicalIF":9.4000,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11211517/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant Communications","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.xplc.2024.100920","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/4/15 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Stress Knowledge Map (SKM; https://skm.nib.si) is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical, signaling, and regulatory molecular interactions in plants: a highly curated model of plant stress signaling (PSS; 543 reactions) and a large comprehensive knowledge network (488 390 interactions). Both were constructed by domain experts through systematic curation of diverse literature and database resources. SKM provides a single entry point for investigations of plant stress response and related growth trade-offs, as well as interactive explorations of current knowledge. PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin. Here, we describe the features of SKM and show, through two case studies, how it can be used for complex analyses, including systematic hypothesis generation and design of validation experiments, or to gain new insights into experimental observations in plant biology.

胁迫知识图谱:用于植物胁迫反应系统生物学分析的知识图谱资源。
胁迫知识图谱(SKM, https://skm.nib.si)是一个公开可用的资源,包含两个互补的知识图谱,描述了当前有关植物中生化、信号和调控分子相互作用的知识:一个是高度编辑的植物胁迫信号模型(PSS,543 个反应),另一个是大型综合知识网络(CKN,488,390 个相互作用)。这两个模型都是由领域专家通过系统整理各种文献和数据库资源而构建的。SKM 为植物胁迫反应研究和相关生长权衡以及当前知识的交互式探索提供了一个单一的切入点。PSS 也被制定为系统生物学的定性和定量模型,因此是植物数字孪生的起点。在此,我们将介绍 SKM 的特点,并通过两个案例研究说明如何将其用于复杂的分析,包括系统假设的生成、验证实验的设计,或获得对植物生物学实验观察的新见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Plant Communications
Plant Communications Agricultural and Biological Sciences-Plant Science
CiteScore
15.70
自引率
5.70%
发文量
105
审稿时长
6 weeks
期刊介绍: Plant Communications is an open access publishing platform that supports the global plant science community. It publishes original research, review articles, technical advances, and research resources in various areas of plant sciences. The scope of topics includes evolution, ecology, physiology, biochemistry, development, reproduction, metabolism, molecular and cellular biology, genetics, genomics, environmental interactions, biotechnology, breeding of higher and lower plants, and their interactions with other organisms. The goal of Plant Communications is to provide a high-quality platform for the dissemination of plant science research.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信