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The molecular substrates of IPAH are poorly understood while diagnostics and therapeutics innovation remain as unmet needs for this debilitating disease. In this study, a network-based methodology was used to uncover the salient molecular mechanisms of IPAH to inform drug and diagnostic discovery, and personalized medicine. Expression profiling datasets associated with IPAH were obtained from the Gene Expression Omnibus database: GSE15197, GSE113439, GSE53408, and GSE67597. The comparative analysis of mRNA and miRNA expression data and the modular analysis of a transcriptome-based weighted gene coexpression network unraveled disease-specific gene and miRNA signatures. DEAD-box helicase 52 (\n                    <jats:italic toggle=\"yes\">DDx52<\/jats:italic>\n                    ), ESF1 nucleolar pre-RNA processing protein (\n                    <jats:italic toggle=\"yes\">ESF1<\/jats:italic>\n                    ), heterogeneous nuclear ribonuclearprotein A3 (\n                    <jats:italic toggle=\"yes\">MNRNPA3<\/jats:italic>\n                    ), Myosin VA (\n                    <jats:italic toggle=\"yes\">MYO5A<\/jats:italic>\n                    ), replication factor C subunit 1 (\n                    <jats:italic toggle=\"yes\">RFC1<\/jats:italic>\n                    ), and arginine and serine rich coiled coil 1 (\n                    <jats:italic toggle=\"yes\">RSRC1<\/jats:italic>\n                    ) were detected as the salient genes for IPAH. In addition, the salient gene-based drug repositioning analysis identified alvespimycin, tanespimycin, geldanamycin, LY294002, cephaeline, digoxigenin, lanatoside C, helveticoside, trichostatin A, phenoxybenzamine, genistein, pioglitazone, and rosiglitazone as potential drug candidates for IPAH. In conclusion, this study provides new molecular signatures in relation to IPAH and attendant potential drug candidates for further experimental and translational clinical research for patients with IPAH.\n                  <\/jats:p>","DOI":"10.1089\/omi.2023.0066","type":"journal-article","created":{"date-parts":[[2023,7,6]],"date-time":"2023-07-06T11:39:51Z","timestamp":1688643591000},"page":"315-326","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Idiopathic Pulmonary Arterial Hypertension: Network-Based Integration of Multi-Omics Data Reveals New Molecular Signatures and Candidate Drugs"],"prefix":"10.1177","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2970-387X","authenticated-orcid":false,"given":"Ceyda","family":"Kasavi","sequence":"first","affiliation":[{"name":"Department of Bioengineering, Faculty of Engineering, Marmara University, Istanbul, Turkey."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2023,7,19]]},"reference":[{"key":"e_1_3_5_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/75556"},{"key":"e_1_3_5_3_1","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbab120"},{"key":"e_1_3_5_4_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-4-2"},{"key":"e_1_3_5_5_1","doi-asserted-by":"publisher","DOI":"10.1093\/neuonc\/nor067"},{"key":"e_1_3_5_6_1","first-page":"175","article-title":"Mining microarray data at NCBI's Gene Expression Omnibus (GEO)","volume":"338","author":"Barrett T","year":"2006","unstructured":"Barrett T, , Edgar R. 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