---
_id: '14449'
abstract:
- lang: eng
text: The rapid development of machine learning (ML) techniques has opened up the
data-dense field of microbiome research for novel therapeutic, diagnostic, and
prognostic applications targeting a wide range of disorders, which could substantially
improve healthcare practices in the era of precision medicine. However, several
challenges must be addressed to exploit the benefits of ML in this field fully.
In particular, there is a need to establish “gold standard” protocols for conducting
ML analysis experiments and improve interactions between microbiome researchers
and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome)
COST Action CA18131 is a European network established in 2019 to promote collaboration
between discovery-oriented microbiome researchers and data-driven ML experts to
optimize and standardize ML approaches for microbiome analysis. This perspective
paper presents the key achievements of ML4Microbiome, which include identifying
predictive and discriminatory ‘omics’ features, improving repeatability and comparability,
developing automation procedures, and defining priority areas for the novel development
of ML methods targeting the microbiome. The insights gained from ML4Microbiome
will help to maximize the potential of ML in microbiome research and pave the
way for new and improved healthcare practices.
acknowledgement: "This study is based upon work from COST Action ML4Microbiome “Statistical
and machine learning techniques in human microbiome studies” (CA18131), supported
by COST (European Cooperation in Science and Technology), www.cost.eu. MB acknowledges
support through the Metagenopolis grant ANR-11-DPBS-0001. IM-I acknowledges support
by the “Miguel Servet Type II” program (CPII21/00013) of the ISCIII-Madrid (Spain),
co-financed by the FEDER.\r\nThe authors are grateful to all COST Action CA18131
“Statistical and machine learning techniques in human microbiome studies” members
for their contribution to the COST Action objectives, and to COST (European Cooperation
in Science and Technology) for the economic support, www.cost.eu. WG2 and WG3 thank
Emmanuelle Le Chatelier and Pauline Barbet (Université Paris-Saclay, INRAE, MetaGenoPolis,
78350, Jouy-en-Josas, France) for preparing the shotgun CRC benchmark dataset."
article_number: '1257002'
article_processing_charge: Yes
article_type: original
author:
- first_name: Domenica
full_name: D’Elia, Domenica
last_name: D’Elia
- first_name: Jaak
full_name: Truu, Jaak
last_name: Truu
- first_name: Leo
full_name: Lahti, Leo
last_name: Lahti
- first_name: Magali
full_name: Berland, Magali
last_name: Berland
- first_name: Georgios
full_name: Papoutsoglou, Georgios
last_name: Papoutsoglou
- first_name: Michelangelo
full_name: Ceci, Michelangelo
last_name: Ceci
- first_name: Aldert
full_name: Zomer, Aldert
last_name: Zomer
- first_name: Marta B.
full_name: Lopes, Marta B.
last_name: Lopes
- first_name: Eliana
full_name: Ibrahimi, Eliana
last_name: Ibrahimi
- first_name: Aleksandra
full_name: Gruca, Aleksandra
last_name: Gruca
- first_name: Alina
full_name: Nechyporenko, Alina
last_name: Nechyporenko
- first_name: Marcus
full_name: Frohme, Marcus
last_name: Frohme
- first_name: Thomas
full_name: Klammsteiner, Thomas
last_name: Klammsteiner
- first_name: Enrique Carrillo De Santa
full_name: Pau, Enrique Carrillo De Santa
last_name: Pau
- first_name: Laura Judith
full_name: Marcos-Zambrano, Laura Judith
last_name: Marcos-Zambrano
- first_name: Karel
full_name: Hron, Karel
last_name: Hron
- first_name: Gianvito
full_name: Pio, Gianvito
last_name: Pio
- first_name: Andrea
full_name: Simeon, Andrea
last_name: Simeon
- first_name: Ramona
full_name: Suharoschi, Ramona
last_name: Suharoschi
- first_name: Isabel
full_name: Moreno-Indias, Isabel
last_name: Moreno-Indias
- first_name: Andriy
full_name: Temko, Andriy
last_name: Temko
- first_name: Miroslava
full_name: Nedyalkova, Miroslava
last_name: Nedyalkova
- first_name: Elena Simona
full_name: Apostol, Elena Simona
last_name: Apostol
- first_name: Ciprian Octavian
full_name: Truică, Ciprian Octavian
last_name: Truică
- first_name: Rajesh
full_name: Shigdel, Rajesh
last_name: Shigdel
- first_name: Jasminka Hasić
full_name: Telalović, Jasminka Hasić
last_name: Telalović
- first_name: Erik
full_name: Bongcam-Rudloff, Erik
last_name: Bongcam-Rudloff
- first_name: Piotr
full_name: Przymus, Piotr
last_name: Przymus
- first_name: Naida Babić
full_name: Jordamović, Naida Babić
last_name: Jordamović
- first_name: Laurent
full_name: Falquet, Laurent
last_name: Falquet
- first_name: Sonia
full_name: Tarazona, Sonia
last_name: Tarazona
- first_name: Alexia
full_name: Sampri, Alexia
last_name: Sampri
- first_name: Gaetano
full_name: Isola, Gaetano
last_name: Isola
- first_name: David
full_name: Pérez-Serrano, David
last_name: Pérez-Serrano
- first_name: Vladimir
full_name: Trajkovik, Vladimir
last_name: Trajkovik
- first_name: Lubos
full_name: Klucar, Lubos
last_name: Klucar
- first_name: Tatjana
full_name: Loncar-Turukalo, Tatjana
last_name: Loncar-Turukalo
- first_name: Aki S.
full_name: Havulinna, Aki S.
last_name: Havulinna
- first_name: Christian
full_name: Jansen, Christian
id: 837b2259-bcc9-11ed-a196-ae55927bc6e2
last_name: Jansen
- first_name: Randi J.
full_name: Bertelsen, Randi J.
last_name: Bertelsen
- first_name: Marcus Joakim
full_name: Claesson, Marcus Joakim
last_name: Claesson
citation:
ama: 'D’Elia D, Truu J, Lahti L, et al. Advancing microbiome research with machine
learning: Key findings from the ML4Microbiome COST action. Frontiers in Microbiology.
2023;14. doi:10.3389/fmicb.2023.1257002'
apa: 'D’Elia, D., Truu, J., Lahti, L., Berland, M., Papoutsoglou, G., Ceci, M.,
… Claesson, M. J. (2023). Advancing microbiome research with machine learning:
Key findings from the ML4Microbiome COST action. Frontiers in Microbiology.
Frontiers. https://doi.org/10.3389/fmicb.2023.1257002'
chicago: 'D’Elia, Domenica, Jaak Truu, Leo Lahti, Magali Berland, Georgios Papoutsoglou,
Michelangelo Ceci, Aldert Zomer, et al. “Advancing Microbiome Research with Machine
Learning: Key Findings from the ML4Microbiome COST Action.” Frontiers in Microbiology.
Frontiers, 2023. https://doi.org/10.3389/fmicb.2023.1257002.'
ieee: 'D. D’Elia et al., “Advancing microbiome research with machine learning:
Key findings from the ML4Microbiome COST action,” Frontiers in Microbiology,
vol. 14. Frontiers, 2023.'
ista: 'D’Elia D, Truu J, Lahti L, Berland M, Papoutsoglou G, Ceci M, Zomer A, Lopes
MB, Ibrahimi E, Gruca A, Nechyporenko A, Frohme M, Klammsteiner T, Pau ECDS, Marcos-Zambrano
LJ, Hron K, Pio G, Simeon A, Suharoschi R, Moreno-Indias I, Temko A, Nedyalkova
M, Apostol ES, Truică CO, Shigdel R, Telalović JH, Bongcam-Rudloff E, Przymus
P, Jordamović NB, Falquet L, Tarazona S, Sampri A, Isola G, Pérez-Serrano D, Trajkovik
V, Klucar L, Loncar-Turukalo T, Havulinna AS, Jansen C, Bertelsen RJ, Claesson
MJ. 2023. Advancing microbiome research with machine learning: Key findings from
the ML4Microbiome COST action. Frontiers in Microbiology. 14, 1257002.'
mla: 'D’Elia, Domenica, et al. “Advancing Microbiome Research with Machine Learning:
Key Findings from the ML4Microbiome COST Action.” Frontiers in Microbiology,
vol. 14, 1257002, Frontiers, 2023, doi:10.3389/fmicb.2023.1257002.'
short: D. D’Elia, J. Truu, L. Lahti, M. Berland, G. Papoutsoglou, M. Ceci, A. Zomer,
M.B. Lopes, E. Ibrahimi, A. Gruca, A. Nechyporenko, M. Frohme, T. Klammsteiner,
E.C.D.S. Pau, L.J. Marcos-Zambrano, K. Hron, G. Pio, A. Simeon, R. Suharoschi,
I. Moreno-Indias, A. Temko, M. Nedyalkova, E.S. Apostol, C.O. Truică, R. Shigdel,
J.H. Telalović, E. Bongcam-Rudloff, P. Przymus, N.B. Jordamović, L. Falquet, S.
Tarazona, A. Sampri, G. Isola, D. Pérez-Serrano, V. Trajkovik, L. Klucar, T. Loncar-Turukalo,
A.S. Havulinna, C. Jansen, R.J. Bertelsen, M.J. Claesson, Frontiers in Microbiology
14 (2023).
date_created: 2023-10-22T22:01:16Z
date_published: 2023-09-25T00:00:00Z
date_updated: 2023-12-13T13:07:21Z
day: '25'
ddc:
- '000'
department:
- _id: ScienComp
doi: 10.3389/fmicb.2023.1257002
external_id:
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pmid:
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publication: Frontiers in Microbiology
publication_identifier:
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quality_controlled: '1'
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title: 'Advancing microbiome research with machine learning: Key findings from the
ML4Microbiome COST action'
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legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
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