{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Pappu MAA"],"funding":["King Salman Center for Disability Research"],"pagination":["1459"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12732698"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["16(12)"],"pubmed_abstract":["<b>Background:</b> Parkinson's disease (PD) is a complex neurodegenerative disorder in aged people with multifaceted molecular underpinnings. It poses a severe threat to millions of older adults worldwide. The understanding of the molecular mechanisms of PD development and the performance of its therapeutic strategies has not yet reached a satisfactory level. <b>Methods:</b> This study integrated six transcriptomic datasets to uncover key genes (KGs) and their underlying pathogenic mechanisms, providing insights into potential therapeutic strategies for PD. We designed a comprehensive computational pipeline using various bioinformatics tools and databases to investigate PD-causing KGs, focusing on their functions, pathways, regulatory mechanisms, and potential therapeutic drug molecules. <"],"journal":["Genes"],"pubmed_title":["Multi-Transcriptome-Informed Network Pharmacology Reveals Novel Biomarkers and Therapeutic Candidates for Parkinson's Disease."],"pmcid":["PMC12732698"],"funding_grant_id":["KSRG-2024-120"],"pubmed_authors":["Hossain MS","Noman MA","Azad A","Mollah MNH","Ahmed MF","Latif MA","Alyami SA","Alotaibi N","Sultana MH","Faysal MF","Pappu MAA","Alamin M"],"additional_accession":[]},"is_claimable":false,"name":"Multi-Transcriptome-Informed Network Pharmacology Reveals Novel Biomarkers and Therapeutic Candidates for Parkinson's Disease.","description":"<b>Background:</b> Parkinson's disease (PD) is a complex neurodegenerative disorder in aged people with multifaceted molecular underpinnings. It poses a severe threat to millions of older adults worldwide. The understanding of the molecular mechanisms of PD development and the performance of its therapeutic strategies has not yet reached a satisfactory level. <b>Methods:</b> This study integrated six transcriptomic datasets to uncover key genes (KGs) and their underlying pathogenic mechanisms, providing insights into potential therapeutic strategies for PD. We designed a comprehensive computational pipeline using various bioinformatics tools and databases to investigate PD-causing KGs, focusing on their functions, pathways, regulatory mechanisms, and potential therapeutic drug molecules. <","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Dec","modification":"2026-05-28T03:16:51.029Z","creation":"2026-05-28T03:10:58.774Z"},"accession":"S-EPMC12732698","cross_references":{"pubmed":["41465132"],"doi":["10.3390/genes16121459"]}}