AIMC Topic: Microbiota

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

Briefings in bioinformatics May 20, 2021
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...
Aging Phylogeny Deep Learning Arthritis, Rheumatoid Humans Female Male Microbiota Malawi Sex Factors Twin Studies as Topic Computational Biology Cluster Analysis Models, Biological
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Merged Affinity Network Association Clustering: Joint multi-omic/clinical clustering to identify disease endotypes.

Cell reports Apr 13, 2021
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...
Precision Medicine Female Adult Asthma Humans Transcriptome Case-Control Studies Adolescent Child, Preschool Male Middle Aged Gene Expression Profiling Microbiota Allergens Cluster Analysis Epigenome Child Unsupervised Machine Learning Datasets as Topic Atlases as Topic Feces Nasal Cavity Benchmarking Proteomics Gene Expression Regulation
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Application of deep learning methods in biological networks.

Briefings in bioinformatics Mar 22, 2021
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...
Microbiota Data Mining Drug Delivery Systems Drug Discovery Deep Learning Proteins Drug Interactions Protein Interaction Maps Genotype Neural Networks, Computer Algorithms Phenotype Humans
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MB-GAN: Microbiome Simulation via Generative Adversarial Network.

GigaScience Feb 5, 2021
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...
Proteins Microbiota Computer Simulation Image Processing, Computer-Assisted Humans Neural Networks, Computer
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A system of coordinated autonomous robots for Lagrangian studies of microbes in the oceanic deep chlorophyll maximum.

Science robotics Jan 13, 2021
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...
Humans Ecosystem Environmental Monitoring Acoustics Plankton Robotics Satellite Communications Chlorophyll Oceans and Seas Microbiota Seawater Oceanography Pacific Ocean
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Harnessing machine learning for development of microbiome therapeutics.

Gut microbes Jan 1, 2021
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...
Machine Learning Precision Medicine Microbiota Artificial Intelligence
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EHAI: Enhanced Human Microbe-Disease Association Identification.

Current protein & peptide science Jan 1, 2020
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...
Models, Statistical Microbiota Humans Datasets as Topic Machine Learning Databases, Factual Colorectal Neoplasms ROC Curve Genetic Association Studies
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The scientific events that shaped the decade.

Nature Dec 1, 2019
Humans Social Change Big Data Artificial Intelligence Gravitation Genomics Climate Change Female Bias Physics Gene Editing CRISPR-Cas Systems Infant, Newborn Environmental Policy Conservation of Energy Resources Microbiota
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Compositional data network analysis via lasso penalized D-trace loss.

Bioinformatics (Oxford, England) Sep 15, 2019
MOTIVATION: With the development of high-throughput sequencing techniques for 16S-rRNA gene profiling, the analysis of microbial communities is becoming more and more attractive and reliable. Inferring the direct interaction network among microbial c...
High-Throughput Nucleotide Sequencing Mice Neural Networks, Computer RNA, Ribosomal, 16S Algorithms Microbiota Animals
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