Machine Learning for Metabolic Identification

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A3 Kirjan tai muun kokoomateoksen osa
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2021

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Department of Computer Science

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en

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22

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Abstract

Metabolic identification is an essential part of metabolomics to understand biochemical characteristics of metabolites, which are small molecules that play important functions in biological systems. However, this field remains challenging with many unknown metabolites in existence. Mass spectrometry (MS) is a common technology that deals with such small molecules. Over recent decades, many methods have been proposed for MS-based metabolite identification, but machine learning has been a key process in recent progress in metabolite identification. This chapter provides a survey on computational methods for metabolic identification with the focus on machine learning, with a discussion on potential improvements for this task.

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DOI

10.1007/978-981-16-4457-3_20

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Nguyen, D H, Nguyen, C H & Mamitsuka, H 2021, Machine Learning for Metabolic Identification . in Creative Complex Systems . Springer, pp. 329-350 . https://doi.org/10.1007/978-981-16-4457-3_20

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https://urn.fi/URN:NBN:fi:aalto-202208104768

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[article-cris] Perustieteiden korkeakoulu / SCI