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However, the underlying regulatory processes are only partly understood.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      We assembled regulator binding information from serveral sources to construct a generic human and mouse gene regulatory network. Advancing our \u201cMixed Integer linear Programming based Regulatory Interaction Predictor\u201d (MIPRIP) approach, we identified the most common and cancer-type specific regulators of\n                      <jats:italic>TERT<\/jats:italic>\n                      across 19 different human cancers. The results were validated by using the well-known\n                      <jats:italic>TERT<\/jats:italic>\n                      regulation by the ETS1 transcription factor in a subset of melanomas with mutations in the\n                      <jats:italic>TERT<\/jats:italic>\n                      promoter.\n                    <\/jats:p>\n                    <jats:p>\n                      Our improved MIPRIP2 R-package and the associated generic regulatory networks are freely available at\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/KoenigLabNM\/MIPRIP\">https:\/\/github.com\/KoenigLabNM\/MIPRIP<\/jats:ext-link>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      MIPRIP 2.0 identified common as well as tumor type specific regulators of\n                      <jats:italic>TERT<\/jats:italic>\n                      . The software can be easily applied to transcriptome datasets to predict gene regulation for any gene and disease\/condition under investigation.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-019-3323-2","type":"journal-article","created":{"date-parts":[[2019,12,30]],"date-time":"2019-12-30T08:02:39Z","timestamp":1577692959000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Modelling TERT regulation across 19 different cancer types based on the MIPRIP 2.0 gene regulatory network approach"],"prefix":"10.1186","volume":"20","author":[{"given":"Alexandra M.","family":"Poos","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Theresa","family":"Korda\u00df","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amol","family":"Kolte","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Volker","family":"Ast","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcus","family":"Oswald","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karsten","family":"Rippe","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rainer","family":"K\u00f6nig","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,12,30]]},"reference":[{"issue":"21","key":"3323_CR1","doi-asserted-by":"publisher","first-page":"2801","DOI":"10.1101\/gad.11.21.2801","volume":"11","author":"WE Wright","year":"1997","unstructured":"Wright WE, Tesmer VM, Huffman KE, Levene SD, Shay JW. 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