Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts.
To reveal the respective brain areas, we used a step-wise functional neuroimaging approach in healthy German speaking subjects.
Hypothesis-driven methods, such as the general linear model (GLM), which regress exterior stimulus from voxel-wise functional brain activity, are limited due to overlooking the complexity of brain activities and the diversity of concurrent brain networks.
Group independent component analysis (ICA) was used to decompose fMRI scans into 75 brain networks, from which 12 resting-state networks were identified that had significant voxel-wise functional connectivity to anatomical regions of interest.
These scores measure our confidence in pair-wise functional interactions in the networks produced.
The results we have presented here are based largely on Granger causality a linear technique for estimating pair-wise functional connectivity between neurons.
Sequences sharing similar or conserved features are referred to as homologous sequences, and these features can be used for inferring and scoring protein pair-wise functional connections.
Currently, we are integrating into a single protein-protein functional network, all pair-wise functional interactions obtained from different data sources, including genetic interactions, and functional genomics data, in order to predict functions, where possible, of uncharacterized proteins in the genome and to study the biology of the organism.
Significant differences between the populations in the voxel-wise functional connectivity pattern are shown schematically in Supplementary Fig. 8.
Then region of interest-wise functional connectivity analysis on the significant voxels within each region of interest was performed to compare patient groups and their respective healthy controls.
