AIMC Topic: Microbiota

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The application potential of machine learning and genomics for understanding natural product diversity, chemistry, and therapeutic translatability.

Natural product reports
Covering: up to the end of 2020. The machine learning field can be defined as the study and application of algorithms that perform classification and prediction tasks through pattern recognition instead of explicitly defined rules. Among other areas,...

Microbes and complex diseases: from experimental results to computational models.

Briefings in bioinformatics
Studies have shown that the number of microbes in humans is almost 10 times that of cells. These microbes have been proven to play an important role in a variety of physiological processes, such as enhancing immunity, improving the digestion of gastr...

A novel deep learning method for predictive modeling of microbiome data.

Briefings in bioinformatics
With the development and decreasing cost of next-generation sequencing technologies, the study of the human microbiome has become a rapid expanding research field, which provides an unprecedented opportunity in various clinical applications such as d...

Merged Affinity Network Association Clustering: Joint multi-omic/clinical clustering to identify disease endotypes.

Cell reports
Although clinical and laboratory data have long been used to guide medical practice, this information is rarely integrated with multi-omic data to identify endotypes. We present Merged Affinity Network Association Clustering (MANAclust), a coding-fre...

Application of deep learning methods in biological networks.

Briefings in bioinformatics
The increase in biological data and the formation of various biomolecule interaction databases enable us to obtain diverse biological networks. These biological networks provide a wealth of raw materials for further understanding of biological system...

MB-GAN: Microbiome Simulation via Generative Adversarial Network.

GigaScience
BACKGROUND: Trillions of microbes inhabit the human body and have a profound effect on human health. The recent development of metagenome-wide association studies and other quantitative analysis methods accelerate the discovery of the associations be...

A system of coordinated autonomous robots for Lagrangian studies of microbes in the oceanic deep chlorophyll maximum.

Science robotics
The deep chlorophyll maximum (DCM) layer is an ecologically important feature of the open ocean. The DCM cannot be observed using aerial or satellite remote sensing; thus, in situ observations are essential. Further, understanding the responses of mi...

Harnessing machine learning for development of microbiome therapeutics.

Gut microbes
The last twenty years of seminal microbiome research has uncovered microbiota's intrinsic relationship with human health. Studies elucidating the relationship between an unbalanced microbiome and disease are currently published daily. As such, microb...

EHAI: Enhanced Human Microbe-Disease Association Identification.

Current protein & peptide science
Recently, an increasing number of biological and clinical reports have demonstrated that imbalance of microbial community has the ability to play important roles among several complex diseases concerning human health. Having a good knowledge of disco...