Sentence examples for using mathematical analyses and from inspiring English sources
Inspired by the predictive intelligence of bio-groups, in this paper we design a novel discrete-time model predictive control based flocking protocol, and investigate the role of predictive mechanisms in flocking of multi-agent systems by using mathematical analyses and numerical simulations.
Differences in growth patterns of the two genotypes were compared by using mathematical models, and morphometric analyses of juvenile salmon were performed to detect differences in body shape.
The quantitative and qualitative data were analysed using mathematical modelling and SPSS statistics including ANOVA.
The availability of high amount of biological data has led to the reconstruction of genome-scale metabolic networks for many organisms [ 1– 4] which can be analysed and probed using mathematical and computational methods [ 5, 6].
In this section, we describe the rich and versatile dynamics of crosstalks between ubiquitination and phosphorylation by using mathematical modelling to analyse a number of network motifs largely motivated by the biological findings discussed in previous sections, and are commonly seen in other signalling processes besides the EGFR pathway.
We used mathematical and numerical analyses of the model to investigate how the habitat value of a network is affected by changes in connectivity and habitat quality, and then to examine interactions between multiple modifications.
This model is then analysed and simulated using mathematical techniques.
They used mathematical regression analyses to calculate mutation rates for selected bacteria, and they coded computer programs in Java to compare DNA sequences from newly isolated antibiotic-resistant bacteria.
Analyses of control strategies through computer simulation were performed using mathematical models of wells, flow lines and separation plant.
IVV and LAVB carried out the mathematical analyses and fitting of the linear equations.
They introduced sophisticated mathematical analyses and modeling projects into beginning biology labs (Kohler et al., 2010).
