%0 Conference Paper %A Farrell, Catherine M. %A Murphy, Terence D. %A Curation and Development Team, RefSeq %D 2020 %T Known versus Predicted: RefSeq Functional Elements as a Reference Set of High-Confidence Non-Genic Elements in Mouse %U https://tagc2020.figshare.com/articles/poster/Known_versus_Predicted_RefSeq_Functional_Elements_as_a_Reference_Set_of_High-Confidence_Non-Genic_Elements_in_Mouse/12150210 %R 10.6084/m9.figshare.12150210.v1 %2 https://tagc2020.figshare.com/ndownloader/files/22341672 %K Functional elements %K non-coding elements %K non-genic regions %K Genome annotation improvement %K Gene Regulatory Regions %K NCBI Reference Sequence %K RefSeq data %K mouse genome annotation %K Bioinformatics %K Computational Biology %K Epigenetics (incl. Genome Methylation and Epigenomics) %K Genome Structure and Regulation %K Genomics %X

Presentation of poster 888C at TAGC 2020 Online, as in the uploaded PDF (FarrellCM_TAGC2020_Poster.pdf). This poster describes NCBI RefSeq Functional Elements, a dataset of human and mouse high-confidence non-genic elements that have been experimentally validated in the literature, including gene regulatory regions, structural elements and other well-characterized regions. Details on data structure, access and use are provided, as well as analyses of the mouse dataset showing the genomic locations of these elements relative to genes, and with comparisons to predicted gene regulatory regions from large-scale epigenomic datasets.

This work was done as part of the Authors' official duties as NIH employees and is a Work of the United States Government. Therefore, copyright may not be established in the United States. 17 U.S.C. ยง 105
%I TAGC 2020