2026-10-14 https://api.researchdata.se/oai-pmh

oai:researchdata.se:2024-343/1 2024-08-21 subject:ssif:10203 subject:ssif:102 subject:ssif:1 principal:slug:uppsala-university

info:eu-repo/semantics/other http://purl.org/dc/dcmitype/Dataset https://doi.org/10.57804/y6dd-4f83 Supplementary data for the article "funMotifs: Tissue-specific transcription factor motifs" Supplementary data for the article "funMotifs: Tissue-specific transcription factor motifs" https://orcid.org/0000-0003-0907-5298 Husen Muhammad Umer Nour-al-dain Marzouka https://orcid.org/0000-0002-2033-7829 https://orcid.org/0000-0002-0766-8789 Zeeshan Khaliq Bioinformatics (Computational Biology) Bioinformatik (beräkningsbiologi) We built a framework to identify tissue-specific functional motifs (funMotifs) across the genome based on thousands of annotation tracks obtained from large-scale genomics projects including ENCODE, RoadMap Epigenomics and FANTOM. The annotations were weighted using a logistic regression model trained on regulatory elements obtained from massively parallel reporter assays. Overall, genome-wide predicted motifs of 519 TFs were characterized across fifteen tissue types. funMotifs summarizes the weighted annotations into a functional activity score for each of the predicted motifs. Please read the article the data contributed to for further information: https://doi.org/10.1101/683722. The dataset was originally published in DiVA and moved to SND in 2024. Se engelsk version för beskrivning. Datasetet har ursprungligen publicerats i DiVA och flyttades över till SND 2024. info:eu-repo/semantics/openAccess Uppsala University Uppsala universitet 2021-10-11T00:00:00Z eng