The phrase "a set of populations" is correct and usable in written English.
It can be used when referring to multiple groups of individuals or organisms that share certain characteristics or are studied together in a particular context.
Example: "The researchers analyzed a set of populations to understand the genetic diversity within the species."
Alternatives: "a group of populations" or "a collection of populations".
YHRD is structured by the assignment of each submitted population sample to a set of populations sharing a common linguistic, demographic, genetic or geographic background (metapopulations).
The FLK metric tests the neutrality of polymorphic markers by contrasting their allele frequencies in a set of populations against what would be expected under a neutral evolution scenario.
Testing an hypothesis that a set of populations is a single species is important to conservation management.
In recent years, interest has reverted to population ecology, sometimes in the form of metapopulation models (consisting of a set of populations with migration between them).
Additionally, a TreeMix model for inferring the set of population splits and mixtures in the history of a set of populations was performed using genome-wide allele frequency data in TreeMix (Pickrell and Pritchard 2012).
In this system maximum likelihood estimates of the probability of ancestry from one of a set of populations equate to the joint allele frequency distributions derived from training sets analyzed by the classifier.
Thorough a detailed analysis we have highlighted the statistical superiority of our proposed MiMSABC approach over a set of population based metaheuristics.
The performance of the algorithms is analyzed by means of a set of population statistics that measure different characteristics of the swarms throughout the search process.
To calculate the drop size distribution, both at the steady state and under transient conditions, the drop size spectrum is usually discretised and a set of population balance equations is solved under given initial and boundary conditions.
In Section 2.6 we derive two methods that can estimate a set of population eigenvalues given a set of sample eigenvalues.
A clear advantage of this algorithm is that the end result is not a density description but a set of population eigenvalues.
