From Chaos to Clarity: Deriving Meaningful Biology from Big Data in Plant Pathology

This Focus Issue was inspired by the vast volumes of data now being generated from both laboratory experiments and field studies. These complex, high dimensional data sets demand new analytic approaches. We invited contributions that apply novel statistical, machine learning, or artificial intelligence methods, or that integrate multiple 'omics approaches to reveal new aspects of pathogen biology, host interactions, or emergent system-level properties. The Focus Issue contains 13 articles falling into five broad themes and drawing upon a diverse range of data types, from disease imaging to meta-barcoding data to optical sensing to genetic data to expert knowledge. Together, these papers show how integrating technology, data, and biology is already transforming plant pathology. We hope this Focus Issue inspires new collaborations, new methods, and a continued commitment to turning data into understanding and chaos into clarity. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 "No Rights Reserved" license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2025.