Gut microbiotaGut microbiota, gut microbiome, or gut flora, are the microorganisms, including bacteria, archaea, fungi, and viruses, that live in the digestive tracts of animals. The gastrointestinal metagenome is the aggregate of all the genomes of the gut microbiota. The gut is the main location of the human microbiome. The gut microbiota has broad impacts, including effects on colonization, resistance to pathogens, maintaining the intestinal epithelium, metabolizing dietary and pharmaceutical compounds, controlling immune function, and even behavior through the gut–brain axis.
Human microbiomeThe human microbiome is the aggregate of all microbiota that reside on or within human tissues and biofluids along with the corresponding anatomical sites in which they reside, including the skin, mammary glands, seminal fluid, uterus, ovarian follicles, lung, saliva, oral mucosa, conjunctiva, biliary tract, and gastrointestinal tract. Types of human microbiota include bacteria, archaea, fungi, protists, and viruses. Though micro-animals can also live on the human body, they are typically excluded from this definition.
MicrobiotaMicrobiota are the range of microorganisms that may be commensal, mutualistic, or pathogenic found in and on all multicellular organisms, including plants. Microbiota include bacteria, archaea, protists, fungi, and viruses, and have been found to be crucial for immunologic, hormonal, and metabolic homeostasis of their host. The term microbiome describes either the collective genomes of the microbes that reside in an ecological niche or within the microbes themselves.
Beta diversityIn ecology, beta diversity (β-diversity or true beta diversity) is the ratio between regional and local species diversity. The term was introduced by R. H. Whittaker together with the terms alpha diversity (α-diversity) and gamma diversity (γ-diversity). The idea was that the total species diversity in a landscape (γ) is determined by two different things: the mean species diversity at the local level (α) and the differentiation among local sites (β).
Alpha diversityIn ecology, alpha diversity (α-diversity) is the mean species diversity in a site at a local scale. The term was introduced by R. H. Whittaker together with the terms beta diversity (β-diversity) and gamma diversity (γ-diversity). Whittaker's idea was that the total species diversity in a landscape (gamma diversity) is determined by two different things, the mean species diversity in sites at a more local scale (alpha diversity) and the differentiation among those sites (beta diversity).
Gamma diversityIn ecology, gamma diversity (γ-diversity) is the total species diversity in a landscape. The term was introduced by R. H. Whittaker together with the terms alpha diversity (α-diversity) and beta diversity (β-diversity). Whittaker's idea was that the total species diversity in a landscape (γ) is determined by two different things, the mean species diversity in sites at a more local scale (α) and the differentiation among those sites (β).
Species diversitySpecies diversity is the number of different species that are represented in a given community (a dataset). The effective number of species refers to the number of equally abundant species needed to obtain the same mean proportional species abundance as that observed in the dataset of interest (where all species may not be equally abundant). Meanings of species diversity may include species richness, taxonomic or phylogenetic diversity, and/or species evenness. Species richness is a simple count of species.
Gut–brain axisThe gut–brain axis is the two-way biochemical signaling that takes place between the gastrointestinal tract (GI tract) and the central nervous system (CNS). The term "gut–brain axis" is occasionally used to refer to the role of the gut microbiota in the interplay as well. The "microbiota–gut–brain (MGB or BGM) axis" explicitly includes the role of gut microbiota in the biochemical signaling events that take place between the GI tract and the CNS.
Linear modelIn statistics, the term linear model is used in different ways according to the context. The most common occurrence is in connection with regression models and the term is often taken as synonymous with linear regression model. However, the term is also used in time series analysis with a different meaning. In each case, the designation "linear" is used to identify a subclass of models for which substantial reduction in the complexity of the related statistical theory is possible.
Generalized linear modelIn statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a link function and by allowing the magnitude of the variance of each measurement to be a function of its predicted value. Generalized linear models were formulated by John Nelder and Robert Wedderburn as a way of unifying various other statistical models, including linear regression, logistic regression and Poisson regression.
