Download PDFOpen PDF in browserUtilizing Functional Annotation of Disease Genes for Disease Clustering14 pages•Published: May 1, 2023AbstractWe investigate the task of disease clustering with the functional annotations of disease genes from the Gene Ontology using the biological process aspect. As an unsupervised machine learning step, the clustering task places communities of similar diseases together based on their closeness to one another using functional annotations of their associated genes. The research work and studies for the similarity, relationship, or clustering of human diseases using the functional information associated with the disease genes are limited. This work builds on and benefits from the advances in gene disease association studies; also from the advances in the functional annotations of human disease genes from the Gene Ontology. We validated the experimental results by comparing the intra-cluster and inter-cluster disease similarity with their semantic similarity in the is-a hierarchy in both MeSH and DO disease ontology. The experimental results are highly encouraging and show that we can rely on the functional profiles using the biological process annotations of disease genes for the study of disease clustering and similarity.Keyphrases: bioinformatics, disease clustering, disease similarity and relationship In: Hisham Al-Mubaid, Tamer Aldwairi and Oliver Eulenstein (editors). Proceedings of International Conference on Bioinformatics and Computational Biology (BICOB-2023), vol 92, pages 58-71.
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