PT - JOURNAL ARTICLE AU - Maria Kondratova AU - Emmanuel Barillot AU - Andrei Zinovyev AU - Inna Kuperstein TI - Knowledge Formalization and High-Throughput Data Visualization Using Signaling Network Maps AID - 10.1101/089409 DP - 2016 Jan 01 TA - bioRxiv PG - 089409 4099 - http://biorxiv.org/content/early/2016/11/24/089409.short 4100 - http://biorxiv.org/content/early/2016/11/24/089409.full AB - Graphical representation of molecular biology knowledge in the form of interactive diagrams became widely used in molecular and computational biology. It enables the scientific community to exchange and discuss information on cellular processes described in numerous scientific publications and to interpret high-throughput data. Constructing a signaling network map is a laborious process, therefore application of consistent procedures for representation of molecular processes and accurately organized annotation is essential for generation of a high-quality signaling network map that can be used by various computational tools. We summarize here the major aims and challenges of assembling information in a form of comprehensive maps of molecular interactions and suggest an optimized workflow. We share our experience gained while creating a biological network resource Atlas of Cancer Signaling Network (ACSN) that was successfully applied in several studies. We explain the map construction process. Then we address the problem of user interaction with large signaling maps and suggest to facilitate navigation by hierarchical organization of map structure and by application of semantic zooming principles. In addition, we describe a computational technology using Google Maps API to explore signaling networks in the manner similar to global geographical maps and provide the outline for preparing a biological network for this type of navigation. Nowadays the most demanded application of signaling maps is integration and functional interpretation of high-throughput data. We demonstrate several examples of cancer data visualization in the context of comprehensive signaling network maps.