emiller88

AI coding assistants have made it possible for domain experts to rewrite established scientific software in days. We believe that a wave of AI-driven tool rewrites is coming to bioinformatics. We've published a set of best-practices principles to help people to approach rewrites in the right way. Along the way we fully rewrote and open-sourced the genomics QC tools for RNAseq, the most widely used genomics pipeline, yielding a >60x performance improvement.

There's so many more!

1. `uvx --from git+https://github.com/httpie/cli httpie` 2. https://simonwillison.net/2024/Aug/21/usrbinenv-uv-run/ uv in a shebang

Agreed. I've found https://lunchmoney.app/ really nice.

FYI, we've added support for the framework to nixos-hardware. I appreciate any feedback or improvements anyone has! https://github.com/NixOS/nixos-hardware/blob/master/framewor...

The resource I recommend to people looking to move from wet lab to dry lab stuff is https://www.biostarhandbook.com/. From your post history it looks like you already have some programming experience, so you could skip the first few chapters which are just a linux intro. I don't think it has all the best practices, but I think it's the most comprehensive overview that starts from square 1 and fills in all the gaps no one tells you when you first start, for example the "Common data types" chapter.

My friend has been working on a personal project to do just that! Check it out! Plug - https://plug.af/

Anyone have any thoughts on Firefox vs Brave?