Search results
Results From The WOW.Com Content Network
Masatoshi Nei was born in 1931 Japan, and his lifelong interest in biology and genetics may have its roots in his upbringing on a farm, in a family of farmers. [1] After completing his undergraduate and doctorate degrees in Japan, Nei emigrated to the United States in 1969. [ 1 ]
In bioinformatics, neighbor joining is a bottom-up (agglomerative) clustering method for the creation of phylogenetic trees, created by Naruya Saitou and Masatoshi Nei in 1987. [1] Usually based on DNA or protein sequence data, the algorithm requires knowledge of the distance between each pair of taxa (e.g., species or sequences) to create the ...
Figure 1: Genetic distance map by Cavalli-Sforza et al. (1994) [1] Genetic distance is a measure of the genetic divergence between species or between populations within a species, whether the distance measures time from common ancestor or degree of differentiation. [2]
Minimum evolution is a distance method employed in phylogenetics modeling. ... Saito and Nei's 1987 NJ algorithm far predates the BME criterion of 2000. For two ...
The project for developing this software was initiated by the leadership of Masatoshi Nei in his laboratory at the Pennsylvania State University in collaboration with his graduate student Sudhir Kumar and postdoctoral fellow Koichiro Tamura. [2] Nei wrote a monograph (pp. 130) outlining the scope of the software and presenting new statistical ...
The definition of 'shortest distance' is what differentiates between the different agglomerative clustering methods. In complete-linkage clustering, the link between two clusters contains all element pairs, and the distance between clusters equals the distance between those two elements (one in each cluster) that are farthest away from each ...
The distance matrix can come from a number of different sources, including measured distance (for example from immunological studies) or morphometric analysis, various pairwise distance formulae (such as euclidean distance) applied to discrete morphological characters, or genetic distance from sequence, restriction fragment, or allozyme data.
This method was presented by Cornuet et al. in 1999. [4] It uses genetic distance to assign the individual to the “closest” population. For the interpopulation distances, the individual is assigned as a sample of two alleles; for the shared allele distance, the distance was taken as the average of distances between the individual and the population samples.