Sentence examples for multiple analysis approaches from inspiring English sources

Multiple analysis approaches have been used to prioritize the library for drug-like compounds, for both whole cell screening and target-based approaches.

For these reasons, similar to parcellation of brain areas in other species (e.g., Felleman and Van Essen 1991), parcellation of human brain areas will be a product of the convergence of multiple analysis approaches and modalities.

Our multiple analysis approach is based on eleven different automated alignments, analysed separately under the maximum likelihood criterion.

Our data is combined with the SSU rDNA stored in public databases (available until October 2008) and investigated using the multiple analysis approach as described above.

In our multiple analysis approach, important clades were recovered with much less effort than before, and in many cases, with higher support.

The multiple analysis approach reveals no consistent phylogenetic structure within the macroperforate group, with support for individual nodes being generally low (Fig. 4; see also Additional file 3).

Our multiple analysis approach shows that alignment ambiguities can have a significant impact on branch support obtained by analysis of ITS sequences in Microbotryum, a factor which, as in many molecular phylogenetic analyses, has not been investigated so far.

Since our focus here was to evaluate the multiple analysis approach to infer a phylogenetic structure within planktonic foraminifera and not to place planktonic taxa in an all-foraminiferal phylogeny, we did not include any benthic group.

In this study we have used data derived from nuclear ITS and a multiple analysis approach to sequence alignment to address phylogenetic questions in the parasitic fungal family Microbotryaceae.

Here, we investigate the potential of the multiple analysis approach to infer a molecular phylogeny of all modern planktonic foraminiferal taxa by using a matrix of 146 new and 153 previously published SSU rDNA sequences.

In order to provide an overall view of the functional organization of the face-sensitive areas, it is necessary to conduct a comprehensive study that taps into the pivotal functional properties of all the face-sensitive areas, within the context of the same experimental design, and uses multiple data analysis approaches.