Prediction of protein subplastid localization and origin with PlastoGram
Sidorczuk, Katarzyna (University of Wrocław)
Gagat, Przemysław (University of Wrocław)
Kała, Jakub (Warsaw University of Technology)
Nielsen, Henrik (Technical University of Denmark. Department of Health Technology)
Pietluch, Filip (University of Wrocław)
Mackiewicz, Paweł (University of Wrocław)
Burdukiewicz, Michał (Universitat Autònoma de Barcelona. Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí")

Data:	2023
Resum:	Due to their complex history, plastids possess proteins encoded in the nuclear and plastid genome. Moreover, these proteins localize to various subplastid compartments. Since protein localization is associated with its function, prediction of subplastid localization is one of the most important steps in plastid protein annotation, providing insight into their potential function. Therefore, we create a novel manually curated data set of plastid proteins and build an ensemble model for prediction of protein subplastid localization. Moreover, we discuss problems associated with the task, e. g. data set sizes and homology reduction. PlastoGram classifies proteins as nuclear- or plastid-encoded and predicts their localization considering: envelope, stroma, thylakoid membrane or thylakoid lumen; for the latter, the import pathway is also predicted. We also provide an additional function to differentiate nuclear-encoded inner and outer membrane proteins. PlastoGram is available as a web server at and as an R package at . The code used for described analyses is available at .
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Computational platforms and environments ; Machine learning ; Protein analysis ; Software ; Computational biology and bioinformatics ; Plant sciences
Publicat a:	Scientific reports, Vol. 13 (May 2023) , art. 8365, ISSN 2045-2322

DOI: 10.1038/s41598-023-35296-0
PMID: 37225726

10 p, 1.5 MB

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