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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.
What HN saysHN commenters link the BioJulia response to the Seq language benchmarks, noting it reproduced the results and that BioJulia validates data where Seq does not.
17HN people shared it
7linked it in comments
12stories submitted
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Most-shared posts
- 1On the performance and design of Julia BioSequences compared to the Seq language10 people · 31 points · first shared 2020 · discussion on HN
- 2What scientists must know about hardware to write fast code (2020)6 people · 118 points · first shared 2020 · 29 comments on HN
- 3Homepage2 people · first shared 2019
What HN people wrote when they linked it
xvilka · 2019-10-31
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/
StefanKarpinski · 2020-01-25
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
cbkeller · 2020-01-06
I think these folks are working on it: https://biojulia.net/
dunefox · 2021-09-15
BioJulia might be the better choice since it validates data and seq doesn't: https://biojulia.net/post/seq-lang/
encode · 2021-09-15
Also see this comparison between Julia's BioSequences and Seq by Jakob Nissen and Ben Ward: https://biojulia.net/post/seq-lang/
improbable22 · 2020-02-10
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/
ChrisRackauckas · 2020-01-25
And an interesting note of Biosequences versus the new Seq language: https://biojulia.net/post/seq-lang/