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#singlecellomics — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #singlecellomics, aggregated by home.social.

  1. Pipeline release! nf-core/pixelator v4.0.0 - nf-core/pixelator 4.0.0!
    Pipeline to generate Proximity Network Assay data with Pixelator (Pixelgen Technologies AB)
    Please see the changelog: github.com/nf-core/pixelator/r

    #molecularpixelation #pixelator #pixelgentechnologies #proteins #singlecell #singlecellomics #nfcore #openscience #nextflow #bioinformatics

  2. Pipeline release! nf-core/pixelator v3.0.1 - nf-core/pixelator 3.0.1!
    Pipeline to generate Molecular Pixelation data with Pixelator (Pixelgen Technologies AB)
    Please see the changelog: github.com/nf-core/pixelator/r

    #molecularpixelation #pixelator #pixelgentechnologies #proteins #singlecell #singlecellomics #nfcore #openscience #nextflow #bioinformatics

  3. Pipeline release! nf-core/pixelator v3.0.0 - nf-core/pixelator 3.0.0!
    Pipeline to generate Molecular Pixelation data with Pixelator (Pixelgen Technologies AB)
    Please see the changelog: github.com/nf-core/pixelator/r

    #molecularpixelation #pixelator #pixelgentechnologies #proteins #singlecell #singlecellomics #nfcore #openscience #nextflow #bioinformatics

  4. Pipeline release! nf-core/pixelator v2.3.1 - nf-core/pixelator 2.3.1!
    Pipeline to generate Molecular Pixelation data with Pixelator (Pixelgen Technologies AB)
    Please see the changelog: github.com/nf-core/pixelator/r

    #molecularpixelation #pixelator #pixelgentechnologies #proteins #singlecell #singlecellomics #nfcore #openscience #nextflow #bioinformatics

  5. Pipeline release! nf-core/pixelator v2.3.0 - nf-core/pixelator 2.3.0!
    Pipeline to generate Molecular Pixelation data with Pixelator (Pixelgen Technologies AB)
    Please see the changelog: github.com/nf-core/pixelator/r

    #molecularpixelation #pixelator #pixelgentechnologies #proteins #singlecell #singlecellomics #nfcore #openscience #nextflow #bioinformatics

  6. The Single Cell Omics Market is booming—expected to surge from USD 1.96B in 2024 to USD 6.34B by 2032, at a CAGR of 15.8%. Precision medicine, multi-omics integration, and AI analytics are fueling growth.

    Innovators like Illumina, 10x Genomics, Danaher, BD, CYTENA, and PerkinElmer are leading the way.

    👉 View full report here.
    credenceresearch.com/report/si

    #SingleCellOmics #GenomicInnovation #BiotechResearch

  7. The Single Cell Omics Market is booming—expected to surge from USD 1.96B in 2024 to USD 6.34B by 2032, at a CAGR of 15.8%. Precision medicine, multi-omics integration, and AI analytics are fueling growth.

    Innovators like Illumina, 10x Genomics, Danaher, BD, CYTENA, and PerkinElmer are leading the way.

    👉 View full report here.
    credenceresearch.com/report/si

    #SingleCellOmics #GenomicInnovation #BiotechResearch

  8. Need to integrate #SingleCellOmics datasets? This new paper by SIB's @Carmona et al.
    introduces STACAS, a flexible framework to reduce batch effect in #scrna_seq data by taking advantage of prior cell type knowledge nature.com/articles/s41467-024

  9. Need to integrate #SingleCellOmics datasets? This new paper by SIB's @Carmona et al.
    introduces STACAS, a flexible framework to reduce batch effect in #scrna_seq data by taking advantage of prior cell type knowledge nature.com/articles/s41467-024

  10. Need to integrate #SingleCellOmics datasets? This new paper by SIB's @Carmona et al.
    introduces STACAS, a flexible framework to reduce batch effect in #scrna_seq data by taking advantage of prior cell type knowledge nature.com/articles/s41467-024

  11. Need to integrate #SingleCellOmics datasets? This new paper by SIB's @Carmona et al.
    introduces STACAS, a flexible framework to reduce batch effect in #scrna_seq data by taking advantage of prior cell type knowledge nature.com/articles/s41467-024

  12. Need to integrate #SingleCellOmics datasets? This new paper by SIB's @Carmona et al.
    introduces STACAS, a flexible framework to reduce batch effect in #scrna_seq data by taking advantage of prior cell type knowledge nature.com/articles/s41467-024