Gethsemane

For most DNA it now sits at ~Q20 (1%) which is a big improvement - there was also some hacky stuff like HERRO and duplex sequencing which improved it substantially. For routine genome sequencing it's definitely suitable, and the long-read advantage helps resolve some of those trickier regions

Have you written about your experience anywhere? It would be interesting to see how you approached the research sector as a layperson. Are there any plans to move to in vivo? Best of luck with your research!

With AIs as teachers, I disagree. But with AIs assisting routine grading, filling in the university's assessment_framework_draft_v3_final_FINAL.docx, and otherwise freeing up time to actually focus on students - maybe? Although I fear that any productivity gains will be swallowed up by further reductions in lecturer headcount...

Very nice! I also like working from pandoc where possible - being able to split the output into a latex/typst file as well as a docx is very handy, especially when working with collaborators who are more comfortable with word. I wish markdown would see more support in scientific writing - it would solve so many of the headaches with formatting etc (and reduce microsoft's dominance in research)

Ultimately you're not going to find a service that can guarantee privacy, but your best bet might be to extract DNA at home (though tricky without a centrifuge etc...) and submit it to a standard sequencing provider novogene, plasmidsaurus etc. Realistically, they'll hold onto the data for a couple of months as part of the order, then delete it to clear up space. A bunch of discordant sets of DNA sequence without metadata isn't exactly useful for nefarious purposes! I wouldn't recommend sequencing at home unless you are very enthusiastic...

I somewhat agree, in that most of these life science adjacent demos are essentially "find good drug targets for $DISEASE", which mostly overfit to existing, well-classified drugs and targets. The biggest gains IMO will be in improved connectors with autonomous lab platforms, better sharing and annotation of relevant data sets, and yes also improving the pathway to clinical trials.

At the moment, it feels like releases like this overcommit and overpromise on "PhD level reasoning", which I wouldn't say is the absolute bottleneck in clinical research.

It's also all too easy to arbitrarily label something as "bureaucratic" and demand that it gets razed and rebuilt. I'm sure Palantir has some level of bureaucracy internally with all the new contracts it has won - perhaps we should also rip that apart?

Fact is that a university that must simultaneously handle education, research, publishing, estate management, legal stuff, media coverage, health and safety etc etc etc ends up being somewhat bureaucratic.

A highlight of my time in Turkey was the cats - thank you for your efforts! Antalya had a lot of cat hotels in the park and most looked very healthy.

If I was less lazy I could probably find this answer online, but how do you find the battery life these days? I'd love to make the switch, but that's the only thing holding me back...

I'd love to see some benchmarks for this on some common genomic formats (fa, fq, sam, vcf). Will be doubly interesting to see its applicability to nanopore data - lots of useful data is lost because storing FAST5/POD5 is a pain.

Unfortunately, when you write a program that doesn't wrap output FASTAs, you have a bunch of people telling you off because SOME programs (cough bioperl cough) have hard limits on line length :)