@inbook{bf2927c5d42c4fcaa30156f5e54eb32e,
title = "Computational Approaches for Peroxisomal Protein Localization",
abstract = "Computational approaches are practical when investigating putative peroxisomal proteins and for sub-peroxisomal protein localization in unknown protein sequences. Nowadays, advancements in computational methods and Machine Learning (ML) can be used to hasten the discovery of novel peroxisomal proteins and can be combined with more established computational methodologies. Here, we explain and list some of the most used tools and methodologies for novel peroxisomal protein detection and localization.",
keywords = "Cellular compartments, Machine learning, Peroxisome targeting signal, Sub-organelle localization, Subcellular localization",
author = "Marco Anteghini and {Martins dos Santos}, {Vitor A.P.}",
year = "2023",
month = mar,
day = "24",
doi = "10.1007/978-1-0716-3048-8_29",
language = "English",
isbn = " 9781071630471",
series = "Methods in Molecular Biology",
publisher = "Humana Press",
pages = "405--411",
editor = "Michael Schrader",
booktitle = "Peroxisomes",
address = "United States",
edition = "2",
}