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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.
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.
where A, T, G, and C represent the frequency of occurrence of the equivalent base in a particular sequence in a defined length. A window sliding strategy is used to calculate deviation from C through the genome. In these plots, a positive deviation from C corresponds to lagging strand and negative deviation from C corresponds to leading strand. [8]
The example below assesses another double-heterozygote cross using RrYy x RrYy. As stated above, the phenotypic ratio is expected to be 9:3:3:1 if crossing unlinked genes from two double-heterozygotes. The genotypic ratio was obtained in the diagram below, this diagram will have more branches than if only analyzing for phenotypic ratio.
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. p (A) and q (a) are the allele frequencies.
Although the K a /K s ratio is a good indicator of selective pressure at the sequence level, evolutionary change can often take place in the regulatory region of a gene which affects the level, timing or location of gene expression. K a /K s analysis will not detect such change. It will only calculate selective pressure within protein coding ...
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 ...
The concept of gene co-expression networks was first introduced by Butte and Kohane in 1999 as relevance networks. [6] They gathered the measurement data of medical laboratory tests (e.g. hemoglobin level ) for a number of patients and they calculated the Pearson correlation between the results for each pair of tests and the pairs of tests which showed a correlation higher than a certain level ...