GenExViz: Effective Visualizations of Bioinformatics Data - An Analysis Studies on Cancer Prevention

Tommy Dang

2023

Abstract

Data visualization plays an essential role in analyzing bioinformatics as it can provide a holistic view of the data, facilitate high-dimensional biological data analysis, and uncover the latent relations between proteins. However, current methods can not deal with large and complex multidimensional bioinformatics data. This paper explores the novel marriage of data visualization and user interface for analyzing large gene expression data generated under different tested conditions. In particular, we focus on analyzing and visualizing the gene networks of cancer pathways. Although our work focuses on analyzing cancer datasets, our methodology has more general implications for other bioinformatics data sets in a similar setup.

Paper Citation

in Harvard Style

Dang T. (2023). GenExViz: Effective Visualizations of Bioinformatics Data - An Analysis Studies on Cancer Prevention. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 3: BIOINFORMATICS; ISBN 978-989-758-631-6, SciTePress, pages 301-308. DOI: 10.5220/0011903200003414

in Bibtex Style

@conference{bioinformatics23,
author={Tommy Dang},
title={GenExViz: Effective Visualizations of Bioinformatics Data - An Analysis Studies on Cancer Prevention},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 3: BIOINFORMATICS},
year={2023},
pages={301-308},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011903200003414},
isbn={978-989-758-631-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 3: BIOINFORMATICS
TI - GenExViz: Effective Visualizations of Bioinformatics Data - An Analysis Studies on Cancer Prevention
SN - 978-989-758-631-6
AU - Dang T.
PY - 2023
SP - 301
EP - 308
DO - 10.5220/0011903200003414
PB - SciTePress