AIMC Topic: Microbiota
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DeepToA: an ensemble deep-learning approach to predicting the theater of activity of a microbiome.
Bioinformatics (Oxford, England)
Oct 14, 2022
MOTIVATION: Metagenomics is the study of microbiomes using DNA sequencing. A microbiome consists of an assemblage of microbes that is associated with a 'theater of activity' (ToA). An important question is, to what degree does the taxonomic and funct...
Artificial intelligence accelerates the mining of bioactive small molecules from human microbiome.
Clinical and translational medicine
Aug 1, 2022
Identification of antimicrobial peptides from the human gut microbiome using deep learning.
Nature biotechnology
Jun 1, 2022
Virtifier: a deep learning-based identifier for viral sequences from metagenomes.
Bioinformatics (Oxford, England)
Feb 7, 2022
MOTIVATION: Viruses, the most abundant biological entities on earth, are important components of microbial communities, and as major human pathogens, they are responsible for human mortality and morbidity. The identification of viral sequences from m...
phyLoSTM: a novel deep learning model on disease prediction from longitudinal microbiome data.
Bioinformatics (Oxford, England)
Nov 5, 2021
MOTIVATION: Research shows that human microbiome is highly dynamic on longitudinal timescales, changing dynamically with diet, or due to medical interventions. In this article, we propose a novel deep learning framework 'phyLoSTM', using a combinatio...
Human host status inference from temporal microbiome changes via recurrent neural networks.
Briefings in bioinformatics
Nov 5, 2021
With the rapid increase in sequencing data, human host status inference (e.g. healthy or sick) from microbiome data has become an important issue. Existing studies are mostly based on single-point microbiome composition, while it is rare that the hos...
CoCoNet: an efficient deep learning tool for viral metagenome binning.
Bioinformatics (Oxford, England)
Sep 29, 2021
MOTIVATION: Metagenomic approaches hold the potential to characterize microbial communities and unravel the intricate link between the microbiome and biological processes. Assembly is one of the most critical steps in metagenomics experiments. It con...
DeePhage: distinguishing virulent and temperate phage-derived sequences in metavirome data with a deep learning approach.
GigaScience
Sep 8, 2021
BACKGROUND: Prokaryotic viruses referred to as phages can be divided into virulent and temperate phages. Distinguishing virulent and temperate phage-derived sequences in metavirome data is important for elucidating their different roles in interactio...
The application potential of machine learning and genomics for understanding natural product diversity, chemistry, and therapeutic translatability.
Natural product reports
Jun 23, 2021
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
May 20, 2021
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...
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