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Plant Molecular Biology

An International Journal on Molecular Biology, Molecular Genetics and Biochemistry

Publishing model:
Hybrid

Plant Molecular Biology - Call for Papers: Machine Learning and Modeling in Plant Biology Research

The integration of machine learning and modeling techniques in plant biology research presents a transformative opportunity to revolutionize plant research and ensure sustainable agriculture. This special collection aims to showcase research that leverages computational technologies to gain insights into gene function, biological pathway, plant growth, development, stress responses, and adaptation mechanisms. We encourage submissions that explore innovative applications of machine learning models, data-driven approaches, modeling, and other computational tools to address key challenges in plant biology.

Submissions are invited on topics including, but not limited to:

  • Artificial intelligence applications in plant genomics and phenomics.
  • Computational approaches to understanding plant-environment interactions.
  • Data-driven strategies for studying biotic and abiotic stresses in plants.
  • Prediction and modeling of structures, dynamics, and functions of plant proteins. 
  • Application of machine learning to construct and analyze gene regulatory networks.
  • Analysis methods for plant imaging data.
  • Modeling function and dynamics of plant molecular pathways
  • Computational methods for designing and optimizing synthetic biology experiments and gene editing.
  • Developing machine learning models to diagnose plant diseases and suggest treatments.
  • Computational approaches to integrate various types of plant molecular/-omics data

Researchers are invited to submit their manuscripts no later than 1 August 2024, through the journal's submission site (this opens in a new tab). During the submission process, please select the "Special Collection: Machine Learning and Modeling in Plant Biology Research" option. All submissions will undergo rigorous peer review to ensure the highest standards of scientific quality and relevance.

We look forward to receiving your submissions.

Guest Editors

  • Dong Xu (University of Missouri, USA)
  • Yuko Makita (Maebashi Institute of Technology, Japan)
  • Aalt-Jan van Dijk (University of Amsterdam, Netherlands)

Advisors

  • Walter Gassmann (University of Missouri, USA)
  • Jedrzej Szymanski (Leibniz Institute of Plant Genetics and Crop Plant Research, Germany)

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