@ Icahn School of Medicine at Mount Sinai

3D Network

Visualization and analysis of molecular interaction networks are necessary to achieve fundamental and practical understanding of cellular processes involved in disease; they as well support drug discovery and biomarker identification, and have therefore become key tools in basic and translational research. While networks are increasingly informed by data generated from high-throughput experiments, current tools do not adequately scale with concominant increase in their size and complexity. interactome-CAVE (iCAVE_example_imageiCAVE) is a novel integrative visualization platform that introduces novel sophisticated algorithms to automatically generate intuitive visualizations, leveraged on advanced sterescopic (3D) immersive display technologies to address the scalability limitations of traditional 2D representations. iCAVE utilizes its built-in analyses of network topological properties to enable effective representations that maximize understanding of the underlying network structures in complex networks.

iCAVE has multiple built-in database resources available for user query to generate networks for enabling the integrative visualization of diverse data (e.g. disease, drug, protein, metabolite, phenotype, genotype). Alternatively, the user can utilize iCAVE functionalities for her user-generated data. The iCAVE platform can effectively address the complexities that arise from integrated data analysis within large and dense networks with many data properties (e.g. weight, directionality, color, clusters, pathway memberships). Readily usable and portable between personal computers or CAVE environments, iCAVE provides a freely available resource for gaining novel insights from complex HT datasets. iCAVE is freely available only for academic users. For any other use, contact Zeynep H Gümüş directly.

In order to obtain iCAVE download link please download and fill the iCAVE registration form, which can be found here .

Please send the filled form directly to Zeynep H Gümüş at zeynep.gumus AT mssm.edu.

© Zeynep H Gümüş Lab 2015