10.18453/rosdok_id00002868 Wolfien, Markus Markus Wolfien http://d-nb.info/gnd/1223858677 https://orcid.org/0000-0002-1887-4772 Universität Rostock 2020 004 Data processing Computer sciences 570 Life science 610 Medical sciences Medicine 2020 en http://purl.uni-rostock.de/rosdok/id00002868 urn:nbn:de:gbv:28-rosdok_id00002868-5 The ever-increasing amount and diversity of biological and medical data is a major challenge in computational analyses. Computational methods have to be combined into analysis workflows for seamless, swift, and transparent computation. In this work, numerous workflows were developed for the general processing of bulk RNA sequencing (RNA-Seq), single-cell sequencing experiments, and non-coding RNA identification. Mathematical concepts of machine learning and univariate meta-analyses were successfully implemented to independently investigate the role of cell therapies in cardiac regeneration.