REVIEW article
Front. Plant Sci.
Sec. Plant Physiology
Volume 16 - 2025 | doi: 10.3389/fpls.2025.1597030
The Role of Statistics in Advancing Nitric Oxide Research in Plant Biology: From Data Analysis to Mechanistic Insights
Provisionally accepted
Murtaza Khan1,2*
Halah Fadhil Hussein AL-Hakeem3*- 1Kangwon National University, Chuncheon, Republic of Korea
- 2School of Medicine, Kangwon National University, Chuncheon, Gangwon, Republic of Korea
- 3Department of Applied Science, University of Technology, Iraq, Baghdad, Baghdad, Iraq
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Nitric oxide (NO), a key signaling molecule in plants, induces various biological and biochemical processes, including growth and development, adaptive responses, and signaling pathways. The intricate nature of NO dynamics requires vigorous statistical approaches to guarantee precise data interpretation and significant biological conclusions. This review underscores the importance of statistical methodologies in NO study, discussing experimental design, data collection, and advanced analytical tools. In addition, vital statistical challenges such as high variability in NO measurements, small sample sizes, and complex interactions with other signaling molecules, are investigated along with approaches to alleviate these limitations. New computational techniques, including machine learning, integrative omics approaches, and network-based systems biology, present commanding outlines for identifying NO-mediated regulatory mechanisms. Furthermore, we underscore the necessity for interdisciplinary collaboration, open science practices, and standardized protocols to improve the reproducibility and dependability of NO research. By combining robust statistical methods with advanced computational tools, researchers can gain enhanced insights into NO biology and its effects on plant adaptation and resilience.
Keywords: Nitric Oxide, plant biology, statistical analysis, machine learning, Systems Biology
Received: 20 Mar 2025; Accepted: 13 Jun 2025.
Copyright: © 2025 Khan and AL-Hakeem. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Murtaza Khan, Kangwon National University, Chuncheon, Republic of Korea
Halah Fadhil Hussein AL-Hakeem, Department of Applied Science, University of Technology, Iraq, Baghdad, Baghdad, Iraq
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.