2D adaptive grid-based image analysis approach for biological networks

Alhasson, Haifa F.; Obara, Boguslaw

Abstract

The accurate analysis of biological networks, enabled by the precise capture of their individual components, can reveal important underlying biological principles. Efficient image processing techniques are required to precisely identify and quantify the networks from complex images. In this paper, we present a novel approach for a weighted and undirected graph-based network reconstruction and quantification from 2D images using an adaptive rectangular mesh refinement approach. The proposed approach is able to efficiently identify the organizational principles of the network, capturing the underlying network structure, and computing relevant network topological properties. We validate the proposed approach by comparing it with the state-of-the-art method.

Citation

Alhasson, H. F., & Obara, B. (2023, October). 2D adaptive grid-based image analysis approach for biological networks. Presented at The 16th IEEE International Conference on BioInformatics and BioEngineering., Taichung, Taiwan

• Presentation Conference Type: Conference Paper (published)
• Conference Name: The 16th IEEE International Conference on BioInformatics and BioEngineering.
• Start Date: Oct 31, 2023
• End Date: Nov 2, 2016
• Acceptance Date: Aug 25, 2016
• Online Publication Date: Dec 19, 2016
• Publication Date: Dec 19, 2016
• Deposit Date: Aug 25, 2016
• Publicly Available Date: Aug 25, 2016
• Pages: 230-237
• Series ISSN: 2471-7819
• Book Title: 2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) : 31 October–2 November 2016 Taichung, Taiwan ; proceedings.
• DOI: https://doi.org/10.1109/bibe.2016.17
• Public URL: https://durham-repository.worktribe.com/output/1149879
• Additional Information: Conference dates: 31 October - 2 November 2016