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Manuscripts describing BEDbase and geniml

Components of BEDbase and geniml have been published independently. Here, we showcase the tutorials organized by the manuscript that published them, so if you're reading a paper you can more easily find the relevant features. Find the citation of interest on the left to find links to tutorials published as part of each manuscript.

How to cite BEDbase and geniml

Thanks for citing us! If you use BEDbase, geniml, or their components in your research, here are papers you can cite.

If you use... Please cite ...
region2vec embeddings Gharavi et al. (2021) Bioinformatics
bedspace search and embeddings Gharavi et al. (2024) Bioengineering
scEmbed single-cell embedding framework LeRoy et al. (2024) NAR Genomics and Bioinformatics
geniml region set evaluations Zheng et al. (2024) NAR Genomics and Bioinformatics
geniml hmm module Rymuza et al. (2024) Nucleic Acis Research
bedbase database Unpublished

Full citation information for manuscripts

  • Gharavi et al. (2024). Joint representation learning for retrieval and annotation of genomic interval sets
    Bioengineering. DOI: 10.3390/bioengineering11030263
  • Zheng et al. (2024). Methods for evaluating unsupervised vector representations of genomic regions
    Nucleic Acids Research Genomics and Bioinformatics. DOI: 10.1093/nargab/lqae086
  • Xue et al. (2023). Opportunities and challenges in sharing and reusing genomic interval data
    Frontiers in Genetics. DOI: 10.3389/fgene.2023.1155809
  • Rymuza et al. (2024). Methods for constructing and evaluating consensus genomic interval sets
    Nucleic Acids Research. DOI: 10.1093/nar/gkae685
  • LeRoy et al. (2024). Fast clustering and cell-type annotation of scATACdata with pre-trained embeddings
    Nucleic Acids Research Genomics and Bioinformatics. DOI: 10.1093/nargab/lqae073
  • Gu et al. (2021). Bedshift: perturbation of genomic interval sets
    Genome Biology. DOI: 10.1186/s13059-021-02440-w
  • Gharavi et al. (2021). Embeddings of genomic region sets capture rich biological associations in low dimensions
    Bioinformatics. DOI: 10.1093/bioinformatics/btab439