Topic: BrainTrawler

Joint exploration of behavior, genes and brain structure holds the promise to provide a better understanding of neural circuits than unimodal data analyses. Several consortia provide extensive data resources of different modalities. However, analyses of heteromodal data require the expertise of computer scientists for fusing the different resources into a common space. To tackle this limitation, we extended BrainTrawler, our web-based visual analytics frame work for exploration of neurobiological data of human and mice, with a selection of publicly available gene expression and connectivity da

Investigations of transcriptomic and neuroimaging data imply that the spatial patterning of the brain transcriptome follows broad spatial trends in the brain network architecture, which can be used to study the molecular mechanisms of functional connectivity. However, the sophisticated pre-processing and data fusion workflows involved in heteromodal data analysis often require the expertise of computer scientists. There is a need for tools that facilitate this process to enable research without the need for extensive programming knowledge. To address this problem, we present an extension to ou