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To identify brain sulci, sulcal images were generated by morphologic operations and then separated into different components based on connectivity analysis.
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In this study, the authors propose a study to reproduce the findings reported in Figure 4C/D and Supplementary Figure 1 from a previously published manuscript (Sirota et al. Sci Trans Med, 2010), which aimed at assessing the ability to predict drug repurposing opportunities based on connectivity map data analysis.
Networks were algorithmically constructed based on connectivity, as enabled through Ingenuity Pathway Analysis (Ingenuity Systems, Redwood City, CA).
Spine voxels are clustered based on connectivity, analyzed with subvoxel precision using Rayburst-based shanalysisysis routines [1], and classified into three morphologic types, mushroom, stubby and thin.
Networks were then generated based on connectivity.
Focus gene networks were algorithmically generated based on connectivity.
Gene networks were algorithmically generated based on connectivity.
Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number.
The post-processing step filters or adds nodes based on connectivity criteria.
We algorithmically constructed networks containing the identified genes based on connectivity and known relationships among molecules.
Based on a connectivity analysis which identified cold-dependent contributions of PFC activity with PAG in heat-hyperalgesia we propose that cold-induced pain relief partly results from activation of endogenous descending inhibition of nociception.
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