Exploration of Potential Drug Targets for Parkinson’s via Text Mining and Data Analysis

Zihao Yang, Sixian Wang

2022

Abstract

Parkinson’s disease (PD) is a chronic neurodegenerative disease of the central nerve system around the world. However, the current therapeutic regimens were not always effective. We found gene targets of existing drug and give indications of the potential value of new drugs by text mining and microarray data analysis. We firstly used text mining (“Parkinson’s disease” and “parkinson”) and microarray data analysis (GSE22491) to screen the genes that we want. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, as well as the protein-protein interaction (PPI) network were used to analysis the genes. Gene-drug interaction analysis was finally applied to the significant genes to provide insight into potential drug. As a result, we got 1,116 text mining genes (TMGs) and 4,437 differentially expressed genes (DEGs) through text mining and microarray data analysis. 258 genes were up-regulated genes and 31 genes were down regulated among the genes overlapped between TMGs and DEGs. There are six genes are significantand target 16 existing drugs. In summary, in this study, these six genes (Bax, Apaf-1, BCL2L11, Bcl-2, BCL2L1 and CYCS), associated with apoptosis, are the targets of 16 existing drugs. The finding may shed light on the indication of the drugs indications to Parkinson’s disease.

Paper Citation

in Harvard Style

Yang Z. and Wang S. (2022). Exploration of Potential Drug Targets for Parkinson’s via Text Mining and Data Analysis. In Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare - Volume 1: ICHIH, ISBN 978-989-758-596-8, pages 83-91. DOI: 10.5220/0011231400003438

in Bibtex Style

@conference{ichih22,
author={Zihao Yang and Sixian Wang},
title={Exploration of Potential Drug Targets for Parkinson’s via Text Mining and Data Analysis},
booktitle={Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare - Volume 1: ICHIH,},
year={2022},
pages={83-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011231400003438},
isbn={978-989-758-596-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Health Big Data and Intelligent Healthcare - Volume 1: ICHIH,
TI - Exploration of Potential Drug Targets for Parkinson’s via Text Mining and Data Analysis
SN - 978-989-758-596-8
AU - Yang Z.
AU - Wang S.
PY - 2022
SP - 83
EP - 91
DO - 10.5220/0011231400003438