<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>7(7)</volume><submitter>Fernandez-Gutierrez MM</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>In vitro scratch assays have been widely used to study the influence of bioactive substances on the processes of cell migration and proliferation that are involved in re-epithelialization. The development of high-throughput microscopy and image analysis has enabled scratch assays to become compatible with high-throughput research. However, effective processing and in-depth analysis of such high-throughput image datasets are far from trivial and require integration of multiple image processing and data extraction software tools.&lt;h4>Findings&lt;/h4>We developed and implemented a kinetic re-epithelialization analysis pipeline (KREAP) in Galaxy. The KREAP toolbox incorporates freely available image analysis tools and automatically performs image segmentation and feature extract</pubmed_abstract><journal>GigaScience</journal><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6048990</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>KREAP: an automated Galaxy platform to quantify in vitro re-epithelialization kinetics.</pubmed_title><pmcid>PMC6048990</pmcid><pubmed_authors>van Zessen DBH</pubmed_authors><pubmed_authors>Kleerebezem M</pubmed_authors><pubmed_authors>Stubbs AP</pubmed_authors><pubmed_authors>van Baarlen P</pubmed_authors><pubmed_authors>Fernandez-Gutierrez MM</pubmed_authors></additional><is_claimable>false</is_claimable><name>KREAP: an automated Galaxy platform to quantify in vitro re-epithelialization kinetics.</name><description>&lt;h4>Background&lt;/h4>In vitro scratch assays have been widely used to study the influence of bioactive substances on the processes of cell migration and proliferation that are involved in re-epithelialization. The development of high-throughput microscopy and image analysis has enabled scratch assays to become compatible with high-throughput research. However, effective processing and in-depth analysis of such high-throughput image datasets are far from trivial and require integration of multiple image processing and data extraction software tools.&lt;h4>Findings&lt;/h4>We developed and implemented a kinetic re-epithelialization analysis pipeline (KREAP) in Galaxy. The KREAP toolbox incorporates freely available image analysis tools and automatically performs image segmentation and feature extract</description><dates><release>2018-01-01T00:00:00Z</release><publication>2018 Jul</publication><modification>2026-05-04T16:51:07.423Z</modification><creation>2026-04-07T20:41:24.104Z</creation></dates><accession>S-EPMC6048990</accession><cross_references><pubmed>29961849</pubmed><doi>10.1093/gigascience/giy078</doi></cross_references></HashMap>