Kamil Slowikowski  

@slowkow

Computational biologist. Postdoc studying cancer immunotherapy w/ Chloé Villani and Bo Li. PhD from with and Michael Brenner.

Boston
Vrijeme pridruživanja: prosinac 2009.

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  1. Prikvačeni tweet

    TNF and IL-17A synergistically activate IL-6 and other cytokines. But what factors mediate this synergy? In our latest article, we show CUX1 and IκBζ (NFKBIZ) are key mediators of response to TNF and IL-17A in human synovial fibroblasts. 🎓

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  2. proslijedio/la je Tweet
    28. sij

    (1/7) EXCITED to share our latest work on “Mapping heritability of obesity by brain cell types” went through 727 cell types and identified 22 neuronal cell types enriching for obesity SNPs

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  3. proslijedio/la je Tweet
    28. sij

    Check this out: it's Bowtie2 running in the browser using WebAssembly! 🧬😀 This is still preliminary (I disabled SIMD and threads) but I'd like to figure out how this could be useful as a sandbox on the web; ideas are welcome! cc

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  4. 16. sij

    1. Record violin music 🎻 2. Input violin music 🎻 into a neural network 🕸 and train it to reconstruct the violin music 🎻 3. Input human voice 🗣 into the neural network 🕸 4. Network outputs violin music 🎻 with timbre from human voice 🗣 Cool! 🧊

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  5. proslijedio/la je Tweet
    14. sij
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  6. 26. pro 2019.

    After profiling the code and making a few small changes, harmonypy version 0.0.3 should be just as fast as the original R package. Surprisingly, numba did not seem to speed things up. I might try more speedups again in the future with Cython.

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  7. proslijedio/la je Tweet
    24. pro 2019.

    What healthcare must learn from the aviation industry: a cautionary and timely tale of the consequences of rushing things via self- and pre-certification in industries where consumer safety is critical: 1/n

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  8. 21. pro 2019.

    I ported the Harmony algorithm from R/C++ to Python: 📦 So far, the results seem to be concordant with the original version, but the run time is about 5 times slower.

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  9. proslijedio/la je Tweet

    This is what it’s all about. And yet, basically no one has even seen these figures. We need to communicate this everywhere over and over again. Let’s get started.

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  10. proslijedio/la je Tweet
    9. pro 2019.

    Excited to share our newly published method we call Probe-Seq! With it, you can easily isolate (potentially) any cell type from (potentially) any organism and perform cell type specific bulk RNA-Seq! We used mouse, human, Drosophila, and chick as a proof of concept.

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  11. proslijedio/la je Tweet
    10. pro 2019.

    Vega-Lite 4 is out! 📈 New interactive features (including interactive legends), new transforms (density, regression, quantiles), responsive size, gradient fill, image marks, multiline text + more features / bug fixes. More details and screenshots: . (1/5)

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  12. 8. pro 2019.
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  13. proslijedio/la je Tweet
    5. pro 2019.

    Extremely excited to announce sci-Plex, described in a new paper out today ! Joint work with lab, led by a crack team: , , and . With sci-Plex, we can profile expression in single cells from thousands of samples.

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  14. 3. pro 2019.

    Excited to see how will lower the barrier to entry for We will not need to download, compile, and run commands in the terminal. Instead, run *the same code* (samtools, seqtk, etc. thanks to ) with a helpful user interface in the web browser

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  15. proslijedio/la je Tweet
    26. stu 2019.

    We (with Aviv Regev) want to share with you our preprint scPhere(), a deep generative model embedding of single-cell RNA-Seq profiles on hyperspheres and hyperbolic spaces

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  16. 18. stu 2019.
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  17. 15. stu 2019.

    Informative comparison of nuclear and whole cell transcriptomes by Trygve Bakken et al. from I am impressed that the code is available and nicely organized:

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  18. 15. stu 2019.

    ⭐️ So cool to see a blockchain approach for caching and reusing intermediate results between workflows 🤓 The cache can be shared -- for everyone in your group, institute, or computing environment 🤯

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  19. proslijedio/la je Tweet

    New work with , , and available in preprint! We present some PCA-related analyses (mostly in the ), some pitfalls associated with these analyses, and (very) efficient implementations of solutions. --> thread 1/n

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  20. proslijedio/la je Tweet
    11. stu 2019.

    I'm going to start a thread of companies & execs not understanding that algorithms can still be biased on variables that are not inputs. Machine learning is great at finding latent variables.

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  21. 11. stu 2019.

    Incredible work! This helps me to understand tax rates. Lots of wonderful details to explore in this app 🤓 Designed by a team of talented students! 🙌

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