AIMC Topic: Microbiota

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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 ...

Microbial Dark Matter: from Discovery to Applications.

Genomics, proteomics & bioinformatics
With the rapid increase of the microbiome samples and sequencing data, more and more knowledge about microbial communities has been gained. However, there is still much more to learn about microbial communities, including billions of novel species an...

Ontology-aware deep learning enables ultrafast and interpretable source tracking among sub-million microbial community samples from hundreds of niches.

Genome medicine
The taxonomic structure of microbial community sample is highly habitat-specific, making source tracking possible, allowing identification of the niches where samples originate. However, current methods face challenges when source tracking is scaled ...

Artificial intelligence approaches to human-microbiome protein-protein interactions.

Current opinion in structural biology
Host-microbiome interactions play significant roles in human health and disease. Artificial intelligence approaches have been developed to better understand and predict the molecular interplay between the host and its microbiome. Here, we review rece...

Machine Learning Predicts Biogeochemistry from Microbial Community Structure in a Complex Model System.

Microbiology spectrum
Microbial community structure is influenced by the environment and in turn exerts control on many environmental parameters. We applied this concept in a bioreactor study to test whether microbial community structure contains information sufficient to...

Multimodal deep learning applied to classify healthy and disease states of human microbiome.

Scientific reports
Metagenomic sequencing methods provide considerable genomic information regarding human microbiomes, enabling us to discover and understand microbial diseases. Compositional differences have been reported between patients and healthy people, which co...

Metagenomic Sequencing Analysis for Acne Using Machine Learning Methods Adapted to Single or Multiple Data.

Computational and mathematical methods in medicine
The human health status can be assessed by the means of research and analysis of the human microbiome. Acne is a common skin disease whose morbidity increases year by year. The lipids which influence acne to a large extent are studied by metagenomic ...

Physicochemical properties, antioxidant activities and microbial communities of Ethiopian honey wine, Tej.

Food research international (Ottawa, Ont.)
Ethiopian honey wine, Tej, is spontaneously fermented traditional alcoholic beverage, usually made from honey and "gesho" (Rhamnus prinoides). Till now, limited amount of information is available on the characterization of Tej. Thus, the aim of this ...

A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms.

Scientific reports
Increasing occurrence of harmful algal blooms across the land-water interface poses significant risks to coastal ecosystem structure and human health. Defining significant drivers and their interactive impacts on blooms allows for more effective anal...