Understanding the Role of (Advanced) Machine Learning in Metagenomic Workflows

Thomas Krause; Bruno G. N. Andrade; Haithem Afli; Haiying Wang; Huiru Zheng; Matthias L. Hemmje

doi:10.1007/978-3-030-68007-7_4

Understanding the Role of (Advanced) Machine Learning in Metagenomic Workflows

Thomas Krause, Bruno G. N. Andrade, Haithem Afli, Haiying Wang, Huiru Zheng, Matthias L. Hemmje

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

3 Citations (Scopus)

Abstract

With the rapid decrease in sequencing costs there is an increased research interest in metagenomics, the study of the genomic content of microbial communities. Machine learning has also seen a revolution with regards to versatility and performance in the last decade using techniques like “Deep Learning”. Classical as well as modern machine learning (ML) techniques are already used in key areas within metagenomics. There are however several challenges that may impede broader use of ML and especially deep learning.

This paper provides an overview of machine learning in metagenomics, its challenges and its relationship to biomedical pipelines. Special focus is put on modern techniques such as deep learning. The results are then discussed again in the context of the AI2VIS4BigData reference model to validate its relevancy in this research area.

Original language	English
Title of host publication	AVI 2020 Workshops, AVI-BDA and ITAVIS, 2020, Revised Selected Papers
Subtitle of host publication	Advanced Visual Interfaces. Supporting Artificial Intelligence and Big Data Applications. AVI-BDA 2020, ITAVIS 2020
Publisher	Springer Cham
Pages	56-82
Number of pages	27
Volume	12585
ISBN (Print)	978-3-030-68006-0
DOIs	https://doi.org/10.1007/978-3-030-68007-7_4
Publication status	Published (in print/issue) - 3 Feb 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12585 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

Machine learning
Deep learning
Metagenomics
Big data
AI2VIS4BigData

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-68007-7_4

http://link.springer.com/10.1007/978-3-030-68007-7_4

Cite this

Krause, T., Andrade, B. G. N., Afli, H., Wang, H., Zheng, H., & Hemmje, M. L. (2021). Understanding the Role of (Advanced) Machine Learning in Metagenomic Workflows. In AVI 2020 Workshops, AVI-BDA and ITAVIS, 2020, Revised Selected Papers: Advanced Visual Interfaces. Supporting Artificial Intelligence and Big Data Applications. AVI-BDA 2020, ITAVIS 2020 (Vol. 12585, pp. 56-82). Article Chapter 4 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12585 LNCS). Springer Cham. https://doi.org/10.1007/978-3-030-68007-7_4

Krause, Thomas ; Andrade, Bruno G. N. ; Afli, Haithem et al. / Understanding the Role of (Advanced) Machine Learning in Metagenomic Workflows. AVI 2020 Workshops, AVI-BDA and ITAVIS, 2020, Revised Selected Papers: Advanced Visual Interfaces. Supporting Artificial Intelligence and Big Data Applications. AVI-BDA 2020, ITAVIS 2020. Vol. 12585 Springer Cham, 2021. pp. 56-82 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Krause, T, Andrade, BGN, Afli, H, Wang, H , Zheng, H & Hemmje, ML 2021, Understanding the Role of (Advanced) Machine Learning in Metagenomic Workflows. in AVI 2020 Workshops, AVI-BDA and ITAVIS, 2020, Revised Selected Papers: Advanced Visual Interfaces. Supporting Artificial Intelligence and Big Data Applications. AVI-BDA 2020, ITAVIS 2020. vol. 12585, Chapter 4, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12585 LNCS, Springer Cham, pp. 56-82. https://doi.org/10.1007/978-3-030-68007-7_4

Understanding the Role of (Advanced) Machine Learning in Metagenomic Workflows. / Krause, Thomas; Andrade, Bruno G. N.; Afli, Haithem et al.
AVI 2020 Workshops, AVI-BDA and ITAVIS, 2020, Revised Selected Papers: Advanced Visual Interfaces. Supporting Artificial Intelligence and Big Data Applications. AVI-BDA 2020, ITAVIS 2020. Vol. 12585 Springer Cham, 2021. p. 56-82 Chapter 4 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12585 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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Krause T, Andrade BGN, Afli H, Wang H , Zheng H, Hemmje ML. Understanding the Role of (Advanced) Machine Learning in Metagenomic Workflows. In AVI 2020 Workshops, AVI-BDA and ITAVIS, 2020, Revised Selected Papers: Advanced Visual Interfaces. Supporting Artificial Intelligence and Big Data Applications. AVI-BDA 2020, ITAVIS 2020. Vol. 12585. Springer Cham. 2021. p. 56-82. Chapter 4. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-68007-7_4

Understanding the Role of (Advanced) Machine Learning in Metagenomic Workflows

Abstract

Publication series

Bibliographical note

Keywords

UN SDGs

Access to Document

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Cite this