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. Preprints2017, 2017100018. https://doi.org/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. https://doi.org/10.20944/preprints201710.0018.v1
Agapito, G.; Guzzi, P.H.; Cannataro, M. Challenges and Opportunities for Visualization and Analysis of Graph-Modeled Medical Data. Preprints2017, 2017100018. https://doi.org/10.20944/preprints201710.0018.v1
APA Style
Agapito, G., Guzzi, P.H., & Cannataro, M. (2017). Challenges and Opportunities for Visualization and Analysis of Graph-Modeled Medical Data. Preprints. https://doi.org/10.20944/preprints201710.0018.v1
Chicago/Turabian Style
Agapito, G., Pietro Hiram Guzzi and Mario Cannataro. 2017 "Challenges and Opportunities for Visualization and Analysis of Graph-Modeled Medical Data" Preprints. https://doi.org/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.
Keywords
Biological Network; Graphs; Statistical Analysis
Subject
Computer Science and Mathematics, Computer Vision and Graphics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
