{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T07:56:20Z","timestamp":1775634980032,"version":"3.50.1"},"reference-count":48,"publisher":"Oxford University Press (OUP)","issue":"W1","license":[{"start":{"date-parts":[[2020,5,6]],"date-time":"2020-05-06T00:00:00Z","timestamp":1588723200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000864","name":"Michael J. Fox Foundation","doi-asserted-by":"publisher","award":["14446"],"award-info":[{"award-number":["14446"]}],"id":[{"id":"10.13039\/100000864","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs. Here, we present miEAA 2.0, supporting miRNA input from ten frequently investigated organisms. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miRBase miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualizations such as heatmaps and running sum curves with background distributions. We demonstrate the new features with case studies for human kidney cancer, a biomarker study on Parkinson\u2019s disease from the PPMI cohort, and a mouse model for breast cancer. The tool is freely accessible at: https:\/\/www.ccb.uni-saarland.de\/mieaa2.<\/jats:p>","DOI":"10.1093\/nar\/gkaa309","type":"journal-article","created":{"date-parts":[[2020,4,22]],"date-time":"2020-04-22T07:08:25Z","timestamp":1587539305000},"page":"W521-W528","source":"Crossref","is-referenced-by-count":182,"title":["miEAA 2.0: integrating multi-species microRNA enrichment analysis and workflow management systems"],"prefix":"10.1093","volume":"48","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8223-3750","authenticated-orcid":false,"given":"Fabian","family":"Kern","sequence":"first","affiliation":[{"name":"Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbr\u00fccken, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1967-2918","authenticated-orcid":false,"given":"Tobias","family":"Fehlmann","sequence":"first","affiliation":[{"name":"Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbr\u00fccken, Germany"}]},{"given":"Jeffrey","family":"Solomon","sequence":"first","affiliation":[{"name":"Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbr\u00fccken, Germany"}]},{"given":"Louisa","family":"Schwed","sequence":"first","affiliation":[{"name":"Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbr\u00fccken, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4845-2757","authenticated-orcid":false,"given":"Nadja","family":"Grammes","sequence":"first","affiliation":[{"name":"Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbr\u00fccken, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9330-9290","authenticated-orcid":false,"given":"Christina","family":"Backes","sequence":"first","affiliation":[{"name":"Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbr\u00fccken, Germany"}]},{"given":"Kendall","family":"Van\u00a0Keuren-Jensen","sequence":"first","affiliation":[{"name":"Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2040-1955","authenticated-orcid":false,"given":"David Wesley","family":"Craig","sequence":"first","affiliation":[{"name":"Institute of Translational Genomics, University of Southern California, Los Angeles, CA 90033, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7569-819X","authenticated-orcid":false,"given":"Eckart","family":"Meese","sequence":"first","affiliation":[{"name":"Department of Human Genetics, Saarland University, 66421 Homburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5361-0895","authenticated-orcid":false,"given":"Andreas","family":"Keller","sequence":"first","affiliation":[{"name":"Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbr\u00fccken, Germany"},{"name":"School of Medicine Office, Stanford University, Stanford, CA 94305, USA"},{"name":"Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94304, USA"}]}],"member":"286","published-online":{"date-parts":[[2020,5,6]]},"reference":[{"key":"2020062614041529200_B1","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.cell.2018.03.006","article-title":"Metazoan MicroRNAs","volume":"173","author":"Bartel","year":"2018","journal-title":"Cell"},{"key":"2020062614041529200_B2","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbz111","article-title":"What\u2019s the target: understanding two decades of in silico microRNA-target prediction","author":"Kern","year":"2019","journal-title":"Brief. 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