Rezultati pretraživanja
  1. prije 4 sata

    Great tutorial by Malte Lücken on at the Workshop on Computational Models in Biology and Medicine 2020. Check out the paper: , , .

  2. prije 10 sati
    Odgovor korisnicima

    50mu AFAIK ie ~5cells depending on tissue. So deconvolution using is necessary to get true single cell resolution.

  3. ZipSeq: Barcoding for Real-time Mapping of Single Cell Transcriptomes. ZipSeq uses patterned illumination and photocaged oligonucleotides to serially print barcodes (Zipcodes) onto live cells within intact tissues Ref:

    ZipSeq: Barcoding for Real-time Mapping of Single Cell Transcriptomes.  ZipSeq uses patterned illumination and photocaged oligonucleotides to serially print barcodes (Zipcodes) onto live cells within intact tissues  Ref: http://bit.ly/37ZNrN4  #singlecell #ZipSeq #scRNAseq
    ZipSeq: Barcoding for Real-time Mapping of Single Cell Transcriptomes.  ZipSeq uses patterned illumination and photocaged oligonucleotides to serially print barcodes (Zipcodes) onto live cells within intact tissues  Ref: http://bit.ly/37ZNrN4  #singlecell #ZipSeq #scRNAseq
  4. ZipSeq: Barcoding for Real-time Mapping of Single Cell Transcriptomes. Using ZipSeq, they mapped gene expression in 3 settings: in-vitro wound healing, live lymph node sections & in a live tumor microenvironment (TME) Ref:

    ZipSeq: Barcoding for Real-time Mapping of Single Cell Transcriptomes.  Using ZipSeq, they mapped gene expression in 3 settings: in-vitro wound healing, live lymph node sections & in a live tumor microenvironment (TME)  Ref: http://bit.ly/37ZNrN4  #singlecell #ZipSeq #scRNAseq
  5. prije 16 sati

    They are birds... They are planes... They are ! – mjesto: Johns Hopkins School of Medicine

  6. A single-cell RNAseq atlas of the pathogenic stage of Schistosoma mansoni identifies a key regulator of blood feeding. Ref:

    A single-cell RNAseq atlas of the pathogenic stage of Schistosoma mansoni identifies a key regulator of blood feeding.
  7. prije 21 sat

    We're excited to release a update for the analysis and visualization of data, focussing on Visium and MERFISH, thx . Tutorial at Support for different data types and integration with soon!

  8. What a nice surprise early this morning! Thank you for the really cool T! This was our 1st , and I am excited to see how the field will evolve for next year . Cool!

  9. prije 23 sata

    Learning code 💻 in general and analytics in particular is hard 🤯 At we therefore created a new 👨‍🏫tutorial series👩‍🎓 with notebooks 👍 🔸Tutorial 1/4🔸 Getting started with FASTGenomics Lab 👉 Enjoy! /mp

    https://beta.fastgenomics.org/webclient/ui/#/analyses/detail-analysis-42e3571101184ed78856cbd83adfeb7e
  10. 4. velj

    Single-cell transcriptomic atlas of the human retina identifies cell types associated with age-related macular degeneration Fig. Single-cell transcriptomic analysis reveals human retina diversity | Ref:

    Single-cell transcriptomic analysis reveals human retina diversity. a Study design and sample preparation. Postmortem human retinas were enzymatically dissociated and single-cells were isolated. cDNA single-cell libraries were generated and sequenced. We profiled 20,091 cells across the retinas of three normal individuals using a droplet-based microfluidics scRNA-seq platform. b Sketch of retina cross-section showing
  11. 3. velj

    and I highlighting Nagao Lab's nice paper using for novel approach in - how do we reconcile a traditional paradigm with the emergence of giving us such compelling & swift data to use new ?

  12. 3. velj

    Single-Cell Transcriptomics of Regulatory T Cells Reveals Trajectories of Tissue Adaptation | Fig. Steady-State scRNA-Seq Datasets of CD4+ T Cells from LT and NLT Ref:

    Figure 1. Steady-State scRNA-Seq Datasets of CD4+ T Cells from LT and NLT (A) Experimental design for scRNA-seq data collection. (B) t-SNE representing all Treg and Tmem cells that passed quality control. (C) Genes defining the identity of Treg and Tmem cells in lymphoid and non-lymphoid tissues. Colon and skin were individually compared with their corresponding draining lymph node and spleen cells.
  13. 3. velj

    Single-cell genomic approaches for developing the next generation of immunotherapies. | ⁦ by ⁦ Ref:

    challenges in understanding the cellular effects of immunotherapies
    Single-cell analysis as an engine for driving drug development
  14. 3. velj

    I've spent a lot of time the past two weeks writing and editing R and python code for analysis. Python has eclipsed R. Don't @ me.

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  15. 3. velj

    Dr. Harbour treated my mom's eye cancer. He's an amazing physician, and I'm proud enables his research

  16. 3. velj

    Great News & Views from on a recent paper describing how enabled successful treatment of a patient with DRESS, a rare and severe adverse drug reaction 👇

  17. 3. velj

    It is always been a pleasure to read Pierre-Luc Germain's work. Another amazing benchmarking in analysis providing recommendations for pipelines. A lot happens during analysis in . Don't miss out on this work from & team! 👌

  18. 3. velj

    Mapping human cell phenotypes to genotypes with single-cell genomics. Fig. Human organ maps can resolve disease phenotypes Ref:

  19. 3. velj

    Evaluating the function of immunotherapies by simple parameters, like tumor growth or cell type measurements, limits our ability to outline their precise mechanisms of action. resolves this, by defining the cells and pathways affected by the treatment. (4/6)

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  20. 3. velj

    Join us for our first of 2020 - we're visiting St. Louis, MO for an Symposium, Mar3rd -with notable scientists discussing how they in fields of and more! Register today!

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