[HTML][HTML] Applications of machine learning in human microbiome studies: a review on feature selection, biomarker identification, disease prediction and treatment

LJ Marcos-Zambrano… - Frontiers in …, 2021 - frontiersin.org
The number of microbiome-related studies has notably increased the availability of data on
human microbiome composition and function. These studies provide the essential material …

[HTML][HTML] Microbiome datasets are compositional: and this is not optional

GB Gloor, JM Macklaim, V Pawlowsky-Glahn… - Frontiers in …, 2017 - frontiersin.org
Datasets collected by high-throughput sequencing (HTS) of 16S rRNA gene amplimers,
metagenomes or metatranscriptomes are commonplace and being used to study human …

[HTML][HTML] Gut microbiome dysbiosis in antibiotic-treated COVID-19 patients is associated with microbial translocation and bacteremia

L Bernard-Raichon, M Venzon, J Klein… - Nature …, 2022 - nature.com
Although microbial populations in the gut microbiome are associated with COVID-19
severity, a causal impact on patient health has not been established. Here we provide …

[HTML][HTML] Establishing microbial composition measurement standards with reference frames

JT Morton, C Marotz, A Washburne, J Silverman… - Nature …, 2019 - nature.com
Differential abundance analysis is controversial throughout microbiome research. Gold
standard approaches require laborious measurements of total microbial load, or absolute …

QIIME 2 enables comprehensive end‐to‐end analysis of diverse microbiome data and comparative studies with publicly available data

M Estaki, L Jiang, NA Bokulich… - Current protocols in …, 2020 - Wiley Online Library
QIIME 2 is a completely re‐engineered microbiome bioinformatics platform based on the
popular QIIME platform, which it has replaced. QIIME 2 facilitates comprehensive and fully …

[HTML][HTML] Consistent and correctable bias in metagenomic sequencing experiments

MR McLaren, AD Willis, BJ Callahan - Elife, 2019 - elifesciences.org
Marker-gene and metagenomic sequencing have profoundly expanded our ability to
measure biological communities. But the measurements they provide differ from the truth …

[HTML][HTML] Endometrial microbiota composition is associated with reproductive outcome in infertile patients

I Moreno, I Garcia-Grau, D Perez-Villaroya… - Microbiome, 2022 - Springer
Background Previous evidence indicates associations between the female reproductive tract
microbiome composition and reproductive outcome in infertile patients undergoing assisted …

[HTML][HTML] scCODA is a Bayesian model for compositional single-cell data analysis

M Buettner, J Ostner, CL Mueller, FJ Theis… - Nature …, 2021 - nature.com
Compositional changes of cell types are main drivers of biological processes. Their
detection through single-cell experiments is difficult due to the compositionality of the data …

A novel sparse compositional technique reveals microbial perturbations

C Martino, JT Morton, CA Marotz, LR Thompson… - …, 2019 - Am Soc Microbiol
The central aims of many host or environmental microbiome studies are to elucidate factors
associated with microbial community compositions and to relate microbial features to …

Deep learning and its application in geochemical mapping

R Zuo, Y Xiong, J Wang, EJM Carranza - Earth-science reviews, 2019 - Elsevier
Abstract Machine learning algorithms have been applied widely in the fields of natural
science, social science and engineering. It can be expected that machine learning …