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Schematic overview of the modular structure underlying procedures for gene set enrichment analysis. Gene set enrichment analysis (GSEA) (also called functional enrichment analysis or pathway enrichment analysis) is a method to identify classes of genes or proteins that are over-represented in a large set of genes or proteins, and may have an association with different phenotypes (e.g ...
Enriched uranium is a type of uranium in which the percent composition of uranium-235 (written 235 U) has been increased through the process of isotope separation.Naturally occurring uranium is composed of three major isotopes: uranium-238 (238 U with 99.2732–99.2752% natural abundance), uranium-235 (235 U, 0.7198–0.7210%), and uranium-234 (234 U, 0.0049–0.0059%).
Lab orders in the LIMS module of the GNU Health project.. A laboratory information management system (LIMS), sometimes referred to as a laboratory information system (LIS) or laboratory management system (LMS), is a software-based solution with features that support a modern laboratory's operations.
Enrichment factor, used to describe bodies of mineral ore; Job enrichment, improving work processes and employee environments; Nuclear enrichment, the process of increasing the concentration of nuclear fuel
An important aspect in the study of elliptic curves is devising effective ways of counting points on the curve.There have been several approaches to do so, and the algorithms devised have proved to be useful tools in the study of various fields such as number theory, and more recently in cryptography and Digital Signature Authentication (See elliptic curve cryptography and elliptic curve DSA).
Local regression or local polynomial regression, [1] also known as moving regression, [2] is a generalization of the moving average and polynomial regression. [3] Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced / ˈ l oʊ ɛ s / LOH-ess.
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Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables, with the goal of obtaining the posterior probability of the regression coefficients (as well as other parameters describing the distribution of the regressand) and ultimately allowing the out-of-sample prediction of the regressand (often ...