GediNETPro: Discovering Patterns of Disease Groups

Emma Qumsiyeh, Miray Yazıcı, Malik Yousef, Malik Yousef

2023

Abstract

The GediNET tool is based on the Grouping, Scoring, Modeling (G-S-M) approach for detecting disease-disease association (DDA). In this study, we have developed the pro version, GediNETPro, that utilizes the Cross-Validation (CV) information to detect patterns of disease groups association by applying clustering approaches, such as K-means, extracted from the groups’ ranks over the CV iterations. Additionally, a cluster score is computed to measure its significance to provide a deep analysis of the output of GediNET, yielding new biological knowledge that GediNET did not detect. Further, GediNETPro utilizes a visualization approach, such as a heatmap, to get novel insights and in-depth analysis of the disease groups clusters revealing the relationship between diseases that might be used for developing effective interventions for diagnosing. We have tested GediNETPro on the Breast cancer dataset downloaded from the TCGA database. Results showed deeper insight into the interaction and collective behavior of the DDA, facilitating the identification and association of potential biomarkers.

Paper Citation

in Harvard Style

Qumsiyeh E., Yazıcı M. and Yousef M. (2023). GediNETPro: Discovering Patterns of Disease Groups. 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 195-203. DOI: 10.5220/0011690800003414

in Bibtex Style

@conference{bioinformatics23,
author={Emma Qumsiyeh and Miray Yazıcı and Malik Yousef},
title={GediNETPro: Discovering Patterns of Disease Groups},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 3: BIOINFORMATICS},
year={2023},
pages={195-203},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011690800003414},
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 - GediNETPro: Discovering Patterns of Disease Groups
SN - 978-989-758-631-6
AU - Qumsiyeh E.
AU - Yazıcı M.
AU - Yousef M.
PY - 2023
SP - 195
EP - 203
DO - 10.5220/0011690800003414
PB - SciTePress