Michael Schatz

@mike_schatz

Bloomberg Distinguished Associate Professor of Computer Science and Biology at Johns Hopkins University

JHU, Baltimore, MD
schatz-lab.org
Vrijeme pridruživanja: lipanj 2009.
179 fotografija ili videozapisa Fotografije i videozapisi

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  1. proslijedio/la je Tweet
    prije 17 sati

    Check out our latest paper, and Twitter summary by ! it's been an awesome collaboration over the years

    Check out our new paper in ! Find it here Congrats to from and collaborators plus many others. (1/5)
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    1 proslijeđeni tweet 10 korisnika označava da im se sviđa
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  2. proslijedio/la je Tweet
    prije 11 sati
    Odgovor korisnicima i sljedećem broju korisnika:

    Indeed it has. Excellent

    1 reply 5 proslijeđenih tweetova 6 korisnika označava da im se sviđa
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  3. prije 19 sati

    .'s write up on how adaptive sequencing works by controlling pore voltages in real time. Amazing that we can have so much control over individual molecules of DNA!

    1 reply 44 proslijeđena tweeta 98 korisnika označava da im se sviđa
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  4. prije 20 sati

    UNCALLED works directly from signal data, and complements the amazing work et al also posted today to demonstrate streaming basecalling for a similar capability:

    Read Until to enrich >700 genes to mean 30x coverage on single flowcell. Custom panels (up to 25,600 targets so far) as easy as providing a coordinate file. Read more at - thanks to , and team.
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  5. prije 20 sati

    Very exciting day for "adaptive sequencing" - lets us smash through Poisson coverage distributions to turn 5x coverage into 30x over the regions we are actually interested to see

    1 reply 1 proslijeđeni tweet 20 korisnika označava da im se sviđa
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  6. prije 20 sati

    With it we show how you can reach 30x coverage of a 148 gene cancer panel on a single MinION run to yield SV calling 100% concordant to deep coverage ONT or HiFi reads. Crucially, we find twice the number of SVs using long reads compared to short reads in these cancer genes.

    1 reply 18 proslijeđenih tweetova 29 korisnika označava da im se sviđa
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  7. prije 20 sati

    Introducing "Targeted nanopore sequencing by real-time mapping of raw electrical signal with UNCALLED" with et al. Does selective enrichment and depletion of any targeted genomic region purely in software for sequencing.

    8 replies 142 proslijeđena tweeta 222 korisnika označavaju da im se sviđa
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  8. proslijedio/la je Tweet
    30. sij

    This may be my last tweet for a while about resources, but an important one for colleagues. Please R/T! Here are the CoV sequences from Wuhan and US isolates:

    44 proslijeđena tweeta 49 korisnika označava da im se sviđa
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  9. proslijedio/la je Tweet
    30. sij

    New perspective I wrote for where I argue that cohorts with rich molecular and physiological data may allow to prioritize human-relevant targets for drug development In some cases may allow to skip animal testing and move straight to human trials

    47 proslijeđenih tweetova 131 korisnik označava da mu se sviđa
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  10. 30. sij

    It is a classic CS space-time tradeoff, and with a tiny amount of space overhead (0.1%) we can double the performance over ' optimal suffix array search algorithm. If we allow for more space can push it even faster.

    3 proslijeđena tweeta 8 korisnika označava da im se sviđa
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  11. 30. sij

    We were deeply inspired by The Case for Learned Index Structures by et al (plus conversations with last year): . I see huge potential for these ideas in the future

    1 reply 1 proslijeđeni tweet 11 korisnika označava da im se sviđa
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  12. 30. sij

    Real genomes are shockingly predictable with respect to the ordering of k-mers/suffixes

    5 korisnika označava da im se sviđa
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  13. 30. sij

    CS101 teaches us binary search is the best way to search through large datasets, but with a bit of data modeling we can substantially improve performance

    1 reply 1 proslijeđeni tweet 4 korisnika označavaju da im se sviđa
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  14. 30. sij

    Introducing Sapling: Accelerating Suffix Array Queries with Learned Data Models with and .

    48 proslijeđenih tweetova 102 korisnika označavaju da im se sviđa
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  15. proslijedio/la je Tweet
    27. sij

    HG002 data release from . HiFi, CLR, PromethION, GridION, Hi-C, Strand-seq, opmaps... CC0-licensed. Benchmarking to inform production sequencing recipe

    96 proslijeđenih tweetova 191 korisnik označava da mu se sviđa
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  16. proslijedio/la je Tweet
    22. sij

    Congratulations Zachary B. Lippman of , recipient of the NAS Prize in Food and Agriculture Sciences! His work, which aims to improve crop production, helps to address the challenges of population growth and .

    19 proslijeđenih tweetova 58 korisnika označava da im se sviđa
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  17. proslijedio/la je Tweet
    21. sij

    My interview w is out! We cover SV calling w long reads, the life cycle of tools, why it never hurts to ask for a postdoc you feel unqualified for, and the future for population SV calling!

    34 proslijeđena tweeta 78 korisnika označava da im se sviđa
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  18. proslijedio/la je Tweet
    21. sij

    Ribbon () now officially uses WebAssembly-compiled samtools for reading local bam files! Thanks to !

    1 reply 21 proslijeđeni tweet 82 korisnika označavaju da im se sviđa
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  19. proslijedio/la je Tweet
    9. sij

    Join the next seminar, “Marshaling Public Data for Lean and Powerful Splicing Studies.” of will describe how his team is making large public RNA sequencing datasets easy to use. Jan. 16 at 11:00 a.m. ET. Details:

    National Cancer Institute Center for Cancer Research Logo. Bioinformatics Training and Education Program (BTEP) Distinguished Speaker Series presents: Marshaling Public Data for Lean and Powerful Splicing Studies. Speaker will be Ben Langmead of Johns Hopkins University.
    7 proslijeđenih tweetova 12 korisnika označava da im se sviđa
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  20. proslijedio/la je Tweet
    16. sij

    Are non-communicable diseases (NCDs) communicable? An interesting paper in suggests that NCDs could have a microbial component and if so, might be communicable via the microbiota. Wowsa.

    10 proslijeđenih tweetova 21 korisnik označava da mu se sviđa
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