AIMC Topic: Microbiota

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Human Microbiome-Based Prediction of Health Effects of Foods via Machine Learning.

Journal of agricultural and food chemistry
Food absorption is dependent on the activities of internal microorganisms. When exploring food functionality, considering the food compounds and their metabolites produced by microbial metabolism is crucial. In this study, we developed a machine lear...

Predicting hydrocarbon presence in marine cold seep sediments using machine learning models trained with benthic bacterial 16S rRNA taxonomy.

Microbiology spectrum
UNLABELLED: Hydrocarbon seepage in marine sediments exerts selective pressure on benthic microbiomes. Accordingly, microbial community composition in these sediments can reflect the presence of hydrocarbons, with specific groups being more prolific i...

Digestibility, microbiome dynamics, and biogas generation in anaerobic digestion with integrated additives and artificial intelligence.

Environmental research
Addition of abiotic and biotic factors as single or combined in anaerobic digestion (AD) improves the substrate hydrolysis, microbial nexus, and enzymatic activity. The effect of a single abiotic (salinity, micronutrients, and conductive material) or...

Chronological age estimation from human microbiomes with transformer-based Robust Principal Component Analysis.

Communications biology
Deep learning for microbiome analysis has shown potential for understanding microbial communities and human phenotypes. Here, we propose an approach, Transformer-based Robust Principal Component Analysis(TRPCA), which leverages the strengths of trans...

A computational framework for inferring species dynamics and interactions with applications in microbiota ecology.

NPJ systems biology and applications
We present MBPert, a generic computational framework for inferring species interactions and predicting dynamics in time-evolving ecosystems from perturbation and time-series data. In this work, we contextualize the framework in microbial ecosystem mo...

Prediction of blown pack in vacuum-packaged beef based on microbiome profiles and supervised machine learning.

International journal of food microbiology
The preservation of vacuum-packaged beef products is essential for maintaining shelf life. However, the occurrence of blown pack phenomenon, characterized by the expansion of packaging due to gas production by spoilage microorganisms, is still a chal...

Skin Microbiome alterations in heroin users revealed by full-length 16S rRNA sequencing.

BMC microbiology
BACKGROUND: Identifying key characteristics of unknown suspects, such as age, height, and drug use, is essential for advancing forensic investigations.

Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm.

Journal of proteome research
A major challenge in mass-spectrometry-based metaproteomics is accurately identifying and quantifying biological functions across the full taxonomic lineage of microorganisms. This issue stems from what we refer to as the "shared confidently identifi...

Microbiome-based prediction of allogeneic hematopoietic stem cell transplantation outcome.

Genome medicine
BACKGROUND: Allogeneic hematopoietic stem cell transplantation (HSCT) is potentially curative for hematologic malignancies but is frequently complicated by relapse and immune-mediated complications, such as graft-versus-host disease (GVHD). Emerging ...

Ensemble learning for microbiome-based caries diagnosis: multi-group modeling and biological interpretation from salivary and plaque metagenomic data.

BMC oral health
BACKGROUND: Oral microbiota is a major etiological factor in the development of dental caries. Next-generation sequencing techniques have been widely used, generating vast amounts of data which is underexplored. The advancement of artificial intellig...