Here, we combine high-field functional magnetic resonance imaging at 7 T with novel data-driven and model-based analyses to identify corresponding subregions in humans based on the well-known global connectivity fingerprints in rodents and sensitivity to spatial and non-spatial information.
In order to allow the inclusion of site-specific conditions within the assessment, we implemented GIS-based analyses to identify areas with differing ecosystem potential (EP) into GISCAME.
We conducted sequence-based analyses to identify these amino acid residues by performing a multiple sequence alignment and using the AVANA tool (http://sourceforge.net/projects/avana/) to compare the mutual information between subsets of the alignment for the location of the characteristic sites [17].
Therefore, if the genetic signals underlying gF and gC, two highly heritable and polygenic traits, cluster in known biological pathways, it should be possible to use pathway-based analyses to identify which biological processes are most strongly implicated in these subcomponents of g.
The process uses syntactical and dependency based analyses to automatically identify crosscutting concerns at the requirements level.
Based on our analyses to identify direct target genes of RIN, we successfully identified a number of sites to which RIN binds in the genome of ripening fruit cells by screening the promoters of the genes that are highly upregulated during ripening and also within the DNA fragments prepared by the ChIP with the anti-RIN antibody.
A procedure based on experimental and theoretical analyses to identify critical loading conditions on existing metallic railway bridges is presented.
Paleogenomics, or the reconstruction of the ancestral genome structure of modern species, is based on large-scale comparative genomic analyses to identify shared- and lineage-specific shuffling events, prior founder karyotype reconstruction.
Two strategies were used to combine the gene expression and metabolic data; first using multivariate analyses to identify different groups based on gene expression and metabolic data; second correlating levels of specific metabolites to transcripts to suggest new hypotheses of connections between metabolite levels and the underlying biological processes.
