Alicja Bukat, Marek Bukowicki, Michał Bykowski, Karolina Kuczkowska, Szymon Nowakowski, Anna Śliwińska, Łucja Kowalewska
{"title":"GRANA:一个基于人工智能的工具,用于使用混合智能加速叶绿体颗粒纳米形态分析","authors":"Alicja Bukat, Marek Bukowicki, Michał Bykowski, Karolina Kuczkowska, Szymon Nowakowski, Anna Śliwińska, Łucja Kowalewska","doi":"10.1093/plphys/kiaf212","DOIUrl":null,"url":null,"abstract":"Grana are fundamental structural units of the intricate chloroplast membrane network. Investigating their nanomorphology is essential for understanding photosynthetic efficiency regulation. Here, we present GRANA (Graphical Recognition and Analysis of Nanostructural Assemblies), an AI-enhanced, user-friendly software tool that recognizes grana on thylakoid network electron micrographs and generates a complex set of their structural parameters. GRANA employs three artificial neural networks of different architectures and binds them in a one-click workflow. Its output is designed to facilitate hybrid intelligence analysis, securing fast and reliable results from large datasets. The GRANA tool is over 100 times faster compared with currently used manual approaches. As a proof of concept, we have successfully applied GRANA software to diverse grana structures across different land plant species grown under various conditions, demonstrating the wide range of potential applications for our software. GRANA tool supports large-scale analysis of grana nanomorphological features, facilitating advancements in photosynthesis-oriented studies.","PeriodicalId":20101,"journal":{"name":"Plant Physiology","volume":"134 1","pages":""},"PeriodicalIF":6.5000,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GRANA: An AI-based tool for accelerating chloroplast grana nanomorphology analysis using hybrid intelligence\",\"authors\":\"Alicja Bukat, Marek Bukowicki, Michał Bykowski, Karolina Kuczkowska, Szymon Nowakowski, Anna Śliwińska, Łucja Kowalewska\",\"doi\":\"10.1093/plphys/kiaf212\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Grana are fundamental structural units of the intricate chloroplast membrane network. Investigating their nanomorphology is essential for understanding photosynthetic efficiency regulation. Here, we present GRANA (Graphical Recognition and Analysis of Nanostructural Assemblies), an AI-enhanced, user-friendly software tool that recognizes grana on thylakoid network electron micrographs and generates a complex set of their structural parameters. GRANA employs three artificial neural networks of different architectures and binds them in a one-click workflow. Its output is designed to facilitate hybrid intelligence analysis, securing fast and reliable results from large datasets. The GRANA tool is over 100 times faster compared with currently used manual approaches. As a proof of concept, we have successfully applied GRANA software to diverse grana structures across different land plant species grown under various conditions, demonstrating the wide range of potential applications for our software. GRANA tool supports large-scale analysis of grana nanomorphological features, facilitating advancements in photosynthesis-oriented studies.\",\"PeriodicalId\":20101,\"journal\":{\"name\":\"Plant Physiology\",\"volume\":\"134 1\",\"pages\":\"\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2025-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Plant Physiology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/plphys/kiaf212\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PLANT SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant Physiology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/plphys/kiaf212","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PLANT SCIENCES","Score":null,"Total":0}
GRANA: An AI-based tool for accelerating chloroplast grana nanomorphology analysis using hybrid intelligence
Grana are fundamental structural units of the intricate chloroplast membrane network. Investigating their nanomorphology is essential for understanding photosynthetic efficiency regulation. Here, we present GRANA (Graphical Recognition and Analysis of Nanostructural Assemblies), an AI-enhanced, user-friendly software tool that recognizes grana on thylakoid network electron micrographs and generates a complex set of their structural parameters. GRANA employs three artificial neural networks of different architectures and binds them in a one-click workflow. Its output is designed to facilitate hybrid intelligence analysis, securing fast and reliable results from large datasets. The GRANA tool is over 100 times faster compared with currently used manual approaches. As a proof of concept, we have successfully applied GRANA software to diverse grana structures across different land plant species grown under various conditions, demonstrating the wide range of potential applications for our software. GRANA tool supports large-scale analysis of grana nanomorphological features, facilitating advancements in photosynthesis-oriented studies.
期刊介绍:
Plant Physiology® is a distinguished and highly respected journal with a rich history dating back to its establishment in 1926. It stands as a leading international publication in the field of plant biology, covering a comprehensive range of topics from the molecular and structural aspects of plant life to systems biology and ecophysiology. Recognized as the most highly cited journal in plant sciences, Plant Physiology® is a testament to its commitment to excellence and the dissemination of groundbreaking research.
As the official publication of the American Society of Plant Biologists, Plant Physiology® upholds rigorous peer-review standards, ensuring that the scientific community receives the highest quality research. The journal releases 12 issues annually, providing a steady stream of new findings and insights to its readership.