Machine learning in marine ecology: an overview of techniques and applications

P Rubbens, S Brodie, T Cordier… - ICES Journal of …, 2023 - academic.oup.com
Abstract Machine learning covers a large set of algorithms that can be trained to identify
patterns in data. Thanks to the increase in the amount of data and computing power …

Computational analysis of microbial flow cytometry data

P Rubbens, R Props - MSystems, 2021 - Am Soc Microbiol
Flow cytometry is an important technology for the study of microbial communities. It grants
the ability to rapidly generate phenotypic single-cell data that are both quantitative …

Predicting the performance of chain elongating microbiomes through flow cytometric fingerprinting

K Sabbe, L D'Haen, N Boon, R Ganigué - Water Research, 2023 - Elsevier
As part of the circular bio-economy paradigm shift, waste management and valorisation
practices have moved away from sanitation and towards the production of added-value …

[HTML][HTML] Opportunities in optical and electrical single-cell technologies to study microbial ecosystems

F Mermans, V Mattelin, R Van den Eeckhoudt… - Frontiers in …, 2023 - frontiersin.org
New techniques are revolutionizing single-cell research, allowing us to study microbes at
unprecedented scales and in unparalleled depth. This review highlights the state-of-the-art …

[HTML][HTML] Tracking defined microbial communities by multicolor flow cytometry reveals tradeoffs between productivity and diversity

FS Midani, LA David - Frontiers in Microbiology, 2023 - frontiersin.org
Cross feeding between microbes is ubiquitous, but its impact on the diversity and
productivity of microbial communities is incompletely understood. A reductionist approach …

Bacterial, phytoplankton, and viral distributions and their biogeochemical contexts in meromictic Lake Cadagno offer insights into the Proterozoic Ocean microbial loop

JS Saini, C Hassler, R Cable, M Fourquez, F Danza… - MBio, 2022 - Am Soc Microbiol
Lake Cadagno, a permanently stratified high-alpine lake with a persistent microbial bloom in
its chemocline, has long been considered a model for the low-oxygen, high-sulfide …

[HTML][HTML] Recent advances in microbial community analysis from machine learning of multiparametric flow cytometry data

BDÖ Duygan, JR van der Meer - Current Opinion in Biotechnology, 2022 - Elsevier
Highlights•Large multiparametric flow cytometry data sets are ideal for machine learning.•
Unsupervised clustering methods highlight microbial community changes.•Supervised …

Machine learning for understanding inland water quantity, quality, and ecology

AP Appling, SK Oliver, JS Read, JM Sadler, J Zwart - 2022 - eartharxiv.org
This chapter provides an overview of machine learning models and their applications to the
science of inland waters. Such models serve a wide range of purposes for science and …

Convergence of flow cytometry and bacteriology. Current and future applications: a focus on food and clinical microbiology

R Marcos-Fernández, B Sánchez, L Ruiz… - Critical reviews in …, 2023 - Taylor & Francis
Since its development in the 1960s, flow cytometry (FCM) was quickly revealed a powerful
tool to analyse cell populations in medical studies, yet, for many years, was almost …

[HTML][HTML] Domestic hot-water boilers harbour active thermophilic bacterial communities distinctly different from those in the cold-water supply

T Egli, L Campostrini, M Leifels, HP Füchslin, C Kolm… - Water Research, 2024 - Elsevier
Running cold and hot water in buildings is a widely established commodity. However,
interests regarding hygiene and microbiological aspects had so far been focussed on cold …