The alternative algorithms can be implemented for a range of different genomic predictions models, including random regression BLUP (best linear unbiased prediction) and most Bayesian genomic prediction models.
K-means clustering (MATLAB, 2009b, The MathWorks; squared euclidean distance measure) was implemented for a range of k clusters (k = 2-20).
K-means clustering (MATLAB, 2009b; The MathWorks), using squared euclidean distance measure, and performing a preliminary clustering phase on a random 10% subsample of the matrix, was implemented for a range of k clusters (k = 2 20) for both DMA1 and DMA2 pairwise matrices.
Our general model is flexible such that multiple dispersal scenarios could be implemented for a wide range of species to improve our understanding and predictions of species persistence under future global change.
The STORK framework presented here provides a method that can be easily implemented for a wide range of applications, including embryo grading.
In raaSAFT both homonuclear and heteronuclear models are implemented for a wide range of compounds spanning from linear alkanes, to more complicated fluids such as water and alcohols, all the way up to nonionic surfactants and models of asphaltenes and resins.
However, the platform is not limited to this category; it potentially can be implemented for a wide range of services from music streaming to online dating.
One area where this is likely to be particularly critical is for behaviour-based pain assessment schemes that have been developed and implemented for a wide range of animal species [1] [10].
As the method is based on kinetics and is easy to implement for a wide range of substrates, it is a very promising way to numerically predict the effect of design parameters on the efficiency of an anaerobic CSTR.
Next-generation sequencing, however, delivers much more information at affordable costs, and it is easy to implement for a wider range of applications.
Available tools are abundant, designed for varying data types and implemented using a range of different statistical tests: given a set of biological entities, these OMICs signals are then translated into a set of significant pathways and processes (reviewed in Khatri et al., Huang et al. ).
