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    BioJulia

    biojulia.net · Company blog · on HN since 2019

    BioJulia is a community project building bioinformatics tools in Julia, and its blog covers performance, design, and hardware for scientific code.

    Visit blogHN submissions
    ScienceLanguages & CompilersSystems & Performance
    What HN says

    HN commenters link the BioJulia response to the Seq language benchmarks, noting it reproduced the results and that BioJulia validates data where Seq does not.

    Stats for nerds
    17HN people shared it
    12linked in comments
    149story points
    Sep 2021last shared
    2019people per year2021

    Top posts on HN

    1. 1
      What scientists must know about hardware to write fast code (2020)
      6 people · 118 points · first shared 2020 · 29 comments on HN
    2. 2
      On the performance and design of Julia BioSequences compared to the Seq language
      10 people · 31 points · first shared 2020 · Discussion on HN
    3. 3
      Homepage
      2 people · first shared 2019

    What HN people wrote when they linked it

    • StefanKarpinskiJan 2020

      Response from the BioJulia developers: https://biojulia.net/post/seq-lang/. High-level points:

      * they were able reproduce the performance comparison between Seq and BioJulia

      * BioJulia spends most of its time on these benchmarks validating and transcoding data into a more compact, efficient representation of gene sequences

      * Seq, on the other hand, operates on the raw ASCII input data and does no validation

      * BioJulia devs implemented Julia types that representing gene sequences the same way as Seq does in less than 100 lines of Julia code [1]

      * when using the same representation in as Seq, BioJulia was significantly faster than Seq

      * BioJulia devs were able to further optimize transcoding of gene sequences to get a 10x performance improvement [2]

      * with these improvements BioJulia reaches similar performance to Seq while still doing validation and using less memory

      The full post is well worth reading. For me the main takeaway is that there's no real need for a domain-specific language at least not based on these results. Julia is already a great language for this kind of work and you get C-like speed and JIT compilation for free.

      [1] https://github.com/jakobnissen/SeqLangBenchmarks/blob/master/SeqJL.jl

      [2] https://github.com/BioJulia/BioSequences.jl/issues/86

    • xvilkaOct 2019

      You certainly should check the Biostar Handbook[1] then and their forum[2]. BioJulia[3] is worth checking as well (I have really high hopes for Julia language).

      [1] https://www.biostarhandbook.com/

      [2] https://www.biostars.org/

      [3] https://biojulia.net/

    • improbable22Feb 2020

      Not my field, but at least some of it appears to be worked on seriously. This was an interesting recent blog post about making DNA-sequence processing go fast:

      https://biojulia.net/post/seq-lang/

    • encodeSep 2021

      Also see this comparison between Julia's BioSequences and Seq by Jakob Nissen and Ben Ward: https://biojulia.net/post/seq-lang/

    • dunefoxSep 2021

      BioJulia might be the better choice since it validates data and seq doesn't: https://biojulia.net/post/seq-lang/

    • ChrisRackauckasJan 2020

      And an interesting note of Biosequences versus the new Seq language: https://biojulia.net/post/seq-lang/

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