Hyejung Won

@hyejung_won

Assistant Professor at the University of North Carolina, Chapel Hill

Vrijeme pridruživanja: prosinac 2018.

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  1. proslijedio/la je Tweet
    30. sij
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  2. proslijedio/la je Tweet
    23. sij

    Stoked to share our new paper! We use stem cell-derived 3D to track dynamics across human forebrain development ~ with , Nasa, & the whole team 🙏

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  3. proslijedio/la je Tweet
    17. sij

    "Hi-C coupled MAGMA (H-MAGMA), that converts SNP-level summary statistics into gene-level association statistics by assigning non-coding SNPs to their cognate genes based on chromatin interactions"

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  4. proslijedio/la je Tweet
    22. sij

    UNC Departments of Genetics and Psychiatry are looking to hire a clinician scientist for a tenure track assistant professor position in precision psychiatry. It's a great environment here at UNC, come work with us! 🧠+🧬->

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  5. proslijedio/la je Tweet
    20. sij

    Everything you always wanted to know about topological associated chromatin domains!

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  6. proslijedio/la je Tweet
    17. sij

    Tenure-track position @ UNC in human/mammalian genetics, genomics and/or computational biology. Encouraging applicants with a quantitative bent and a record of commitment to inclusion and diversity: . Please RT.

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  7. proslijedio/la je Tweet
    16. sij

    Very excited to announce our work on GWAS of ASD in is now out on .

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  8. proslijedio/la je Tweet
    15. sij

    Let the games begin. Curtis Arledge kicking off the day with a powerful message about autism research and the importance of collaboration.

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  9. proslijedio/la je Tweet
    14. sij

    My blog post from 2017 which I converted to a bioRxiv pre-print last year has now been peer reviewed and published in Nature Biotechnology : "Droplet scRNA-seq is not zero-inflated"

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  10. proslijedio/la je Tweet
    10. sij

    Our new article on using Hi-C to understand Alzheimer's Disease-associated variants. A great collaboration with led by Nana Matoba. Looking forward to many more joint projects between our labs.

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  11. proslijedio/la je Tweet
    6. sij

    It's a big day for ! Our Method of the Year is revealed and it's single-cell multimodal omics!!! Although it doesn't quite roll off the tongue, it is a very exciting time for single-cell biology. Check out our content in the January issue

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  12. proslijedio/la je Tweet
    3. sij

    Congrats to the 2019 NeuroSpark research team awardees, including Natasha Snider!

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    In order to understand the countless N of gene-gene and gene-epigenome interactions we need far better insights of the genome. This review by and Reike Kempfer is the map to help get us there. From HiC to 5C and beyond

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  14. proslijedio/la je Tweet

    So many common genomic threads across 8 neuropsychiatric conditions from this analysis of > 725,000 people by + a big collaborative network

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  15. proslijedio/la je Tweet
    12. pro 2019.

    Remarkable team effort with 100s of collaborators: cross-disorder genetics across 8 psych disorders (N = 727K) Analyses led by Phil Lee, w/ Ken Kendler + many more

    , , i još njih 6
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  16. proslijedio/la je Tweet
    10. pro 2019.

    Congratulations to Drs. Lily and Yuh-Nung Jan for receiving the 20th Perl-UNC Neuroscience Prize!! For the discovery and functional characterization of potassium channels.

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  17. proslijedio/la je Tweet
    9. pro 2019.
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  18. proslijedio/la je Tweet
    5. pro 2019.

    After two years on the BioRxiv and now including 2 years of progress, our paper making the case for random DNA genomics is now available! We found all sorts of cool things, but, to me, the most important is the sheer abundance of transcription factor binding sites. thread->

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  19. proslijedio/la je Tweet
    4. pro 2019.

    A team including Aviv Regev has developed the “Gigantic Parallel Reporter Assay” (GPRA) to measure the expression level associated with each of tens or hundreds of millions of random DNA sequences per experiment. Via :

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  20. proslijedio/la je Tweet
    2. pro 2019.

    I am excited to share our latest work, in which we tackle the question: How can we predict which enhancers regulate which genes in which cell types? Thread 👇 1/

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