Expression‐based machine learning models for predicting plant tissue identity

Our data-driven results highlight that the assertion that knowledge from <i>Arabidopsis</i> is translatable to other plants is not always true. Considering the current landscape of abundant sequencing data, we should reevaluate the scientific emphasis on <i>Arabidopsis</i> and prioritize plant diversity.

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Publication Details

Journal
Applications in Plant Sciences
Published
2024-10-19
DOI
https://doi.org/10.1002/aps3.11621
Citations
3
Primary Topic
Plant Molecular Biology Research
Type
article
Field-Weighted Citation Impact
1.80

Funders

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article

Expression‐based machine learning models for predicting plant tissue identity

Alejandra Rougon‐Cardoso, Sarah Percival, A. López-Hernández, Eddy Mendoza-Galindo et al.
3 citations
Applications in Plant Sciences
Plant Molecular Biology Research
1.80
article

Expression‐based machine learning models for predicting plant tissue identity

Alejandra Rougon‐Cardoso, Sarah Percival, A. López-Hernández, Eddy Mendoza-Galindo, Aman Y. Husbands, Paulo Izquierdo, Nicholas A. Johnson, Francisco Xavier Guerra‐Castillo, Wendy Leuenberger, Robin Waterman, Patricia Basurto‐Lozada, Daniel H. Chitwood, Elizabeth Munch, Sourabh Palande, MacKenzie Jacobs, Arjun Krishnan, Harry Shomer, Beronda L. Montgomery, Brandon Webster, Kara C. Dobson, Damián Villaseñor‐Amador, Sofía Zorrilla‐Azcué, Anne K. Steensma, Brianna N.I. Brown, María Fernanda Guerrero-Carrillo, Héctor Herrera‐Orozco, Asia T. Hightower, Alicia Luckie‐Duque, David Cruz Plancarte, Sidney C. Sitar, Andrew Bleich, Sophia F. Buysse, Noelle A. Connors, Camila Martínez‐Avila, Sikta Das Adhikari, Robert VanBuren, Madison Whyte, Sophia Harlow, Jeremy Arsenault, Jenny M. Schuster, Joanne Elise Thomson
article en
3 citations

Abstract

Our data-driven results highlight that the assertion that knowledge from <i>Arabidopsis</i> is translatable to other plants is not always true. Considering the current landscape of abundant sequencing data, we should reevaluate the scientific emphasis on <i>Arabidopsis</i> and prioritize plant diversity.

Applications in Plant SciencesVol. 13(1)
Mexican Social Security Institute (MX), Universidad Autónoma de la Ciudad de México (MX), Grinnell College (US), Universidad de Morelia (MX), Instituto Tecnológico de León (MX), University of Colorado Anschutz Medical Campus (US), University of Pennsylvania (US), Michigan State University (US), Universidad Nacional Autónoma de México (MX)
National Science Foundation, U.S. Department of Agriculture, Michigan State University, College of Engineering, Michigan State University
Zero hunger
Openalex Percentile: Top 13%
Plant Molecular Biology Research
1.80
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