Expression-based Machine Learning Models for Predicting Plant Tissue Identity
Sourabh Palande, Jeremy Arsenault,Patricia Basurto-Lozada,Andrew Bleich,Brianna N. I. Brown, Sophia F. Buysse,Noelle A. Connors,Sikta Das Adhikari,Kara C. Dobson,Francisco Xavier Guerra-Castillo, Maria F. Guerrero-Carrillo, Sophia Harlow, Hector Herrera-Orozco,Asia T. Hightower,Paulo Izquierdo,Mackenzie Jacobs, Nicholas A. Johnson,Wendy Leuenberger, Alessandro Lopez-Hernandez, Alicia Luckie-Duque, Camila Martinez-Avila,Eddy J. Mendoza-Galindo, David Cruz Plancarte,Jenny M. Schuster,Harry Shomer, Sidney C. Sitar,Anne K. Steensma, Joanne Elise Thomson, Damian Villasenor-Amador,Robin Waterman,Brandon M. Webster, Madison Whyte, Sofia Zorilla-Azcue,Beronda L. Montgomery,Aman Y. Husbands,Arjun Krishnan,Sarah Percival,Elizabeth Munch,Robert Vanburen,Daniel H. Chitwood,Alejandra Rougon-Cardoso Applications in plant sciences（2024）
Key words
Arabidopsis,flowering plants,gene expression,machine learning,model species,tissue identity
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