Sentence examples for methods for population from inspiring English sources

Considering the constant improvement of noninvasive genetic sampling techniques, the importance of search-encounter methods for population monitoring is bound to increase.

Our implementation of a reaction-diffusion model here further reveals some issues regarding continuum methods for population and infectious disease models that suggest consideration of discrete spatial methods (e.g., agent-based) for future work.

Foremost among these new methods for population structure inference is the Bayesian Markov chain Monte Carlo (MCMC) method that has been deployed in the software STRUCTURE [11].

This discordance was necessary because, at present, there is no Bayesian MCMC procedure for automatic assignment that treats dominant data properly (STRUCTURE accepts dominant data, but K must be determined manually), and methods for population structure inference are typically compared using co-dominant data.

A comparison of genetic and standard indirect methods for population estimation of various species shows that both over and under estimation of the true population size occurs with the latter [22]-[25 [22]-[25t the genetic method can yield more precise results as well as information on group membership and movements [26].

This suggests that new methods for population control, such as immuno-contraceptives, could be investigated to substitute for culling.

Expert-based exposure assessment as used in this study is among the best methods for population-based case-control studies.

This problem is partly attributable to the limitations of the methods for population-based measurement of maternal mortality, which cannot be readily overcome by low resource countries due to numerous socio-economic, infrastructural and cultural barriers [ 2, 3].

The direct simulation Monte Carlo (DSMC) method for population balance modeling is capable of retaining the history of each simulation particle and is thus able to deal with multivariate properties in a simple and straightforward manner.

A new event-driven constant-volume (EDCV) method for population balance modeling is proposed to describe the dynamic evolution in dispersed systems under influence of coagulation, breakage, nucleation, surface growth/dissolution (condensation/evaporation) and deposition (settling).

It is expected to become a promising and basic method for population genetics and disease association studies.