AIMC Topic: Microbiota

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Investigation of machine learning algorithms for taxonomic classification of marine metagenomes.

Microbiology spectrum
Taxonomic profiling of microbial communities is essential to model microbial interactions and inform habitat conservation. This work develops approaches in constructing training/testing data sets from publicly available marine metagenomes and evaluat...

EnsDeepDP: An Ensemble Deep Learning Approach for Disease Prediction Through Metagenomics.

IEEE/ACM transactions on computational biology and bioinformatics
A growing number of studies show that the human microbiome plays a vital role in human health and can be a crucial factor in predicting certain human diseases. However, microbiome data are often characterized by the limited samples and high-dimension...

DL-TODA: A Deep Learning Tool for Omics Data Analysis.

Biomolecules
Metagenomics is a technique for genome-wide profiling of microbiomes; this technique generates billions of DNA sequences called reads. Given the multiplication of metagenomic projects, computational tools are necessary to enable the efficient and acc...

Unlocking the microbial studies through computational approaches: how far have we reached?

Environmental science and pollution research international
The metagenomics approach accelerated the study of genetic information from uncultured microbes and complex microbial communities. In silico research also facilitated an understanding of protein-DNA interactions, protein-protein interactions, docking...

Comprehensive Functional Annotation of Metagenomes and Microbial Genomes Using a Deep Learning-Based Method.

mSystems
Comprehensive protein function annotation is essential for understanding microbiome-related disease mechanisms in the host organisms. However, a large portion of human gut microbial proteins lack functional annotation. Here, we have developed a new m...

The need for an integrated multi-OMICs approach in microbiome science in the food system.

Comprehensive reviews in food science and food safety
Microbiome science as an interdisciplinary research field has evolved rapidly over the past two decades, becoming a popular topic not only in the scientific community and among the general public, but also in the food industry due to the growing dema...

Interpretable machine learning framework reveals microbiome features of oral disease.

Microbiological research
BACKGROUND: Although the oral microbiome plays an important role in the progression of oral diseases, the microbes closely related to these diseases remain largely uncharacterized.

The hiatus between organism and machine evolution: Contrasting mixed microbial communities with robots.

Bio Systems
Mixed microbial communities, usually composed of various bacterial and fungal species, are fundamental in a plethora of environments, from soil to human gut and skin. Their evolution is a paradigmatic example of intertwined dynamics, where not just t...

MB-SupCon: Microbiome-based Predictive Models via Supervised Contrastive Learning.

Journal of molecular biology
Human microbiome consists of trillions of microorganisms. Microbiota can modulate the host physiology through molecule and metabolite interactions. Integrating microbiome and metabolomics data have the potential to predict different diseases more acc...

RNN-VirSeeker: A Deep Learning Method for Identification of Short Viral Sequences From Metagenomes.

IEEE/ACM transactions on computational biology and bioinformatics
Viruses are the most abundant biological entities on earth, and play vital roles in many aspects of microbial communities. As major human pathogens, viruses have caused huge mortality and morbidity to human society in history. Metagenomic sequencing ...