Sentence examples for microarray deconvolution that from inspiring English sources

There are several limitations of microarray deconvolution that bear discussion.

These data include expression of genes in different activation and differentiation states that represent a spectrum of cell species present in blood, providing a basis set for microarray deconvolution of blood samples.

Here we use microarray deconvolution to explore immune cell subsets and activation states in SLE patient blood.

Microarray deconvolution is an emerging method for measuring proportions of cell types or states in complex systems.

Another limitation of microarray deconvolution is the discrete nature of the component cell types in the basis set.

A biological sample from a patient with an autoimmune disease typically contains various different immune cell subsets, and the process of microarray deconvolution can quantify their relative proportions.

We purified naïve, effector memory and central memory T cells from peripheral blood mononuclear cells (PBMC) and compared the quantification of the T cell subsets by expression microarray deconvolution to their levels determined by cell sorting (FACS).

Lahdesmaki et al. [32] used a Bayesian approach to deconvolution that avoids a priori definition of basis groups and instead estimates them.

There are two major microarray platforms that have been widely used: cDNA microarrays and oligonucleotide microarrays.

This option is particularly useful for storing deconvolution results that require further refinement later.

We propose a neighbourhood-constrained spherical deconvolution approach that is capable of inferring asymmetric fibre orientation distributions (A-fods).