Write-up of #ISMBECCB2023 and our 11th birthday celebrations in Lyon.

Going Large (Language Models) at ISMB2023/@[email protected] http://gigasciencejournal.com/blog/going-large-language-models-at-ismb2023/

We had an excellent #CompMS session at the #ISMBECCB2023 conference last week.

Many thanks to keynote speakers @[email protected], @[email protected], and @[email protected]; all selected speakers; and poster presenters for showcasing the latest computational advances in mass spectrometry, with applications across #proteomics, #metabolomics, #lipidomics, and more.

Névéol: What can we do?
Understand the stakes better.
Facilitate levers like data sharing, shared tasks, and policy.
Write more documentation, for protocols, etc.; elicit audits.

See Cohen-Boulakia et al 2017 Future Gen Comput Syst

#ismbeccb2023
#textmining

Aurélie Névéol:
How can we make clinical NLP more reproducible? Can NLP also help with reproducibility? Even word or sentence tokenization can be inconsistent. Most NLP folks have, at least once, failed to repeat someone else's experiment, or even their own. Sometimes it's due to differences in preprocessing, software versions, training vs test splits, or other boring things. Availability issues, page limits, and the bias toward novelty don't help either.

#ismbeccb2023
#textmining

One perk of attending #ISMBECCB2023 virtually: watching the recording of a keynote I missed instead of the talk I had planned to watch but turned out not to be interested in.

(I guess you could also plug in your headphones and do the same if you're there in person, but that's noticeably ruder.)

Sylwia Szymanska: Word embeddings capture functions of low complexity regions: scientific literature analysis using a transformer-based language model

Low-complexity regions in proteins are biologically important. But there isn't a database or even a list of these relationships. So let's extract them with a language model.
#ismbeccb2023
#textmining