Preprint Article Version 1 This version is not peer-reviewed

Challenges and Opportunities for Visualization and Analysis of Graph-Modeled Medical Data

Version 1 : Received: 3 October 2017 / Approved: 3 October 2017 / Online: 3 October 2017 (16:52:13 CEST)

How to cite: Agapito, G.; Guzzi, P.H.; Cannataro, M. Challenges and Opportunities for Visualization and Analysis of Graph-Modeled Medical Data. Preprints 2017, 2017100018 (doi: 10.20944/preprints201710.0018.v1). Agapito, G.; Guzzi, P.H.; Cannataro, M. Challenges and Opportunities for Visualization and Analysis of Graph-Modeled Medical Data. Preprints 2017, 2017100018 (doi: 10.20944/preprints201710.0018.v1).

Abstract

Graphs are largely used in computer science to model relations, or associations, among entities the compose complex systems. More recently, they found a broad field of application in bioinformatics and medical informatics supporting modelling, analysis of many systems. The applications span from representing interactions among molecules within cells, to model the functions of the brains. In order to support research, algorithms from graph theory that are able to extract knowledge from network should be coupled to efficient visualisation techniques. Although the importance of such topic, we retain that many challenges should be faced in the futures, such as automated pathway and network layout to better match biologists’ needs, the developing of a standard able to give more and better choices to represent nodes, edges finally, the developing of automated mechanism able to improve the network navigation methods that help users manage large and complex networks with the goal to improve the usability.

Subject Areas

Biological Network; Graphs; Statistical Analysis

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