Jun 11, 2012 · A two-stage approach for population identification is to first construct a similarity matrix and then perform clustering. We review a range of common clustering algorithms and …

Download scientific diagram | Solution distribution of each algorithm with five population sizes: (a) R = 300; (b) R =400; (c) R = 500; (d) R =600; (e) R =700. from publication: Application of ...

A two-stage approach for population identification is to first construct a similarity matrix and then perform clustering. We review a range of common clustering algorithms and evaluate their …

The algorithm is based on Needleman-Wunsch algorithm using threads. The proposed algorithm fills the similarity matrix, of the DNA sequences, Row Column, and Diagonal wise (RCD) using …

We have developed flowMeans, a time-efficient and accurate method for automated identification of cell populations in flow cytometry (FCM) data based on K-means clustering.

This paper considers an evolutionary approach for system identification and attempts to show how GAs can be applied in system identification tasks. Some study cases confirm that good …

Mar 31, 2016 · A closely related automated gating algorithm by Aghaeepour et al. [3] called RchyOptimyx uses dynamic programming and optimization techniques from graph theory to …

We describe a structure for representing known variation called a population reference graph (PRG) and a series of algorithms that enable characterization of the genomes present in an …

Recombination of genes using crossover operators represents the main variation within genetic algorithms, while for evolution strategies (adaptive) mutation introduces variation to the …

A two-stage approach for population identification is to first construct a similarity matrix and then perform clustering. We review a range of common clustering algorithms and evaluate their …