Luciana Martins, João Capela, Emanuel Cunha, Marta Sampaio, Oscar Dias
{"title":"diel_models: a python package for systematic integration of day-night cycles into plant genome-scale metabolic models.","authors":"Luciana Martins, João Capela, Emanuel Cunha, Marta Sampaio, Oscar Dias","doi":"10.1093/bioadv/vbaf087","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>In recent years, genome-scale metabolic models have become indispensable tools for studying complex metabolic processes occurring within living organisms. Understanding plants' metabolic behaviour under diel cycles (24-h day-night cycles) is essential to explain their adaptive strategies to different light conditions. However, integrating these cycles in plant GEMs is complex, laborious, time-consuming, and not systematized. Here, we present <i>diel_models</i>, a novel python package that enables the systematization and accurate construction of diel models based on non-diel plant GEMs, tailored for generic and multi-tissue models. <i>diel_models</i> is a lightweight, modular package with minimal dependencies and broad Python compatibility (v3.8+), making it easy to use, integrate into reconstruction pipelines, and extend with community-driven enhancements. It is also supported on all operating systems, including Windows, MacOS, and Linux, ensuring cross-platform compatibility for a wide range of users.</p><p><strong>Availability and implementation: </strong>The code is freely available at https://github.com/BioSystemsUM/diel_models.git and can be installed using the command pip install diel_models.</p>","PeriodicalId":72368,"journal":{"name":"Bioinformatics advances","volume":"5 1","pages":"vbaf087"},"PeriodicalIF":2.4000,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12070391/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioadv/vbaf087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Summary: In recent years, genome-scale metabolic models have become indispensable tools for studying complex metabolic processes occurring within living organisms. Understanding plants' metabolic behaviour under diel cycles (24-h day-night cycles) is essential to explain their adaptive strategies to different light conditions. However, integrating these cycles in plant GEMs is complex, laborious, time-consuming, and not systematized. Here, we present diel_models, a novel python package that enables the systematization and accurate construction of diel models based on non-diel plant GEMs, tailored for generic and multi-tissue models. diel_models is a lightweight, modular package with minimal dependencies and broad Python compatibility (v3.8+), making it easy to use, integrate into reconstruction pipelines, and extend with community-driven enhancements. It is also supported on all operating systems, including Windows, MacOS, and Linux, ensuring cross-platform compatibility for a wide range of users.
Availability and implementation: The code is freely available at https://github.com/BioSystemsUM/diel_models.git and can be installed using the command pip install diel_models.