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One way to visualize the similarity between two protein or nucleic acid sequences is to use a similarity matrix, known as a dot plot. These were introduced by Gibbs and McIntyre in 1970 [1] and are two-dimensional matrices that have the sequences of the proteins being compared along the vertical and horizontal axes.
A De Finetti diagram visualizing genotype frequencies as distances to triangle edges x (AA), y (Aa) and z (aa) in a ternary plot. The curved line are the Hardy–Weinberg equilibria . A Punnett square visualizing the genotype frequencies of a Hardy–Weinberg equilibrium as areas of a square.
Allele frequency, or gene frequency, is the relative frequency of an allele (variant of a gene) at a particular locus in a population, expressed as a fraction or percentage. [1] Specifically, it is the fraction of all chromosomes in the population that carry that allele over the total population or sample size.
Ab Initio gene prediction is an intrinsic method based on gene content and signal detection. Because of the inherent expense and difficulty in obtaining extrinsic evidence for many genes, it is also necessary to resort to ab initio gene finding, in which the genomic DNA sequence alone is systematically searched for certain tell-tale signs of protein-coding genes.
Selection coefficient, usually denoted by the letter s, is a measure used in population genetics to quantify the relative fitness of a genotype compared to other genotypes. . Selection coefficients are central to the quantitative description of evolution, since fitness differences determine the change in genotype frequencies attributable to selecti
The Hill equation can be applied in modelling the rate at which a gene product is produced when its parent gene is being regulated by transcription factors (e.g., activators and/or repressors). [11] Doing so is appropriate when a gene is regulated by multiple binding sites for transcription factors, in which case the transcription factors may ...
Σfxy = 1.g 1 + 0.g 2 + 0.g 3 + 0.g 4 = g 1. Σfx = g 1 + g 2 = p A. Σfy = g 1 + g 2 = p B. The covariance between x and y values is Σfxy - Σfx Σfy = g 1 - p A p B. which is equivalent to the LD coefficient, D, as defined above. It is usually convenient to calculate the correlation rather than the covariance, normalising by the variances:
A gene map helps point out the relative positions of genes and allows researchers to locate regions of interest in the genome. Genes can then be identified quickly and sequenced quickly. [6] Two approaches to generating gene maps (gene mapping) include physical mapping and genetic mapping. Physical mapping utilizes molecular biology techniques ...