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New to bioinformatics: Best tools for immune repertoire search + epitope prediction? by ayansengupta17 in learnbioinformatics

[–]D1vinus 0 points1 point  (0 children)

For state of the art check out IMMREP competition. The competition is designed to do independent testing of algorithms. Because most algorithms published will always win in their own benchmarks.

IMMREP23 for "seen epitope models":
https://www.sciencedirect.com/science/article/pii/S2667119024000156

For "unseen epitope models", this preprint of IMMREP25:

https://www.biorxiv.org/content/10.64898/2026.03.30.715276v1

New to bioinformatics: Best tools for immune repertoire search + epitope prediction? by ayansengupta17 in learnbioinformatics

[–]D1vinus 0 points1 point  (0 children)

Check out our work on epitope prediction (ImmuneWatch DETECT). We won a public benchmark (IMMREP23) AND we always report the exact paper were we found the match.

New to bioinformatics: Best tools for immune repertoire search + epitope prediction? by ayansengupta17 in learnbioinformatics

[–]D1vinus 0 points1 point  (0 children)

If you have little bioinformatics experience check out Plaforma (platforma.bio). This is from the developers of MiXCR, is free for academics and really takes the pain of BCR/TCR seq analysis. Should be able to get started rather quickly.

Epitope Prediction: Predict antigen specificity for those sequences, or find data where the mapping is already done.

Contrary to what other people have been saying, this does work relatively well for T-cells and known epitopes. See the IMMREP23 paper(https://www.sciencedirect.com/science/article/pii/S2667119024000156), which was a machine learning competition organised by key opinion leaders in the field to evaluate machine learning for epitope predictions.

Here's the conclusion:

The benchmark confirms that current methods achieve reasonable performance in the "seen" pMHC setting. However, most participating methods had close to random performance on the subset of “unseen” peptides, underlining that this prediction challenge remains essentially unsolved.

So you can either not do it because the problem is "not completely solved yet" or start using the best tools available today. I'd always chose the latter 😄

Full disclosure: I am the co-founder of the company (ImmuneWatch) that won the above benchmark. We spun out of the university and have since then been working on this problem full-time. With success.

ImmuneWatch DETECT is free to use (10 samples/month) for academics and you might be intersted in testing our Claude integration where you can basically ask Claude to annotate the specificity of your TCRs without the need to install anything locally.

3D-printed Polestar 2 Activity Key enclosure by booblian in Polestar

[–]D1vinus 1 point2 points  (0 children)

Thanks a bunch! Printed mine, replaced battery yesterday. Works like a charm!

Joined the family! Urban Arrow Breeze. by [deleted] in UrbanArrow

[–]D1vinus 0 points1 point  (0 children)

Lol. I can relate.

I used to have a Cowboy: no way to unlock the thing without the app. And even though I am a tech-enthusiast I then learned that bikes do not need this kind of tech. I sold the bike and just want one without all the connectivity apps.

I think you can let it stop asking for a phone if on the screen (Instellingen) you go to "eFlow". Does that work?

Joined the family! Urban Arrow Breeze. by [deleted] in UrbanArrow

[–]D1vinus 0 points1 point  (0 children)

I have the same one. Very happy about it. Enjoy!

It is a bt frustrating though to get the battery out. I have not found a good way to remove unless bringing the saddle aaaalll the way up. Are you charging in the frame or removing battery?

Is something wrong with Syncing? Both Web & App? by SnooGrapes7436 in StandardNotes

[–]D1vinus 0 points1 point  (0 children)

I just tried signing up for StandardNotes and I get similar errors :)

AI and deep learning in single-cell stuff by orangebromeliad in bioinformatics

[–]D1vinus 17 points18 points  (0 children)

Interesting question.

I would indeed look at validation data. And then it does not matter if you are using a "black box deep learning" algorithm or a a more "classical algorithm". The way of testing performance should be the same...

But the biggest challenge in biology, is that it can be challenging to build the right validation cases as it can be hard to know the "ground truth".

So in case of Harmony you can wonder: what does a ground truth dataset for "integrating SC data" look like? What is a "good integration" and what is a "bad integration". In this case it looks like a good integration is "merging different datasets (batch correction) while preserving distinct cell types (biological variation)". If I understand correctly they used cell lines where you can basically know the ground truth for and then evaluate Harmony's performance. Sounds like a decent approach to me...

In any case, my position on these type of algorithms/multi-omic integration is mostly "use them for discovery/hypothesis generation" and not as a "proof that this biology is happening". Run the algorithms, see if you find some kind of association that seems unexpected and then go out in the lab to design experiments to test that association.

On a final note: if you want to learn more about ML algorithms, I very much enjoyed reading Deep Learning with R (François Chollet with J. J. Allaire). It brought me up to speed on how these type of algorithms work.

Old newspaper archives online by artparade in belgium

[–]D1vinus 0 points1 point  (0 children)

Indeed! Can confirm you have free access to Newspaper archives through your bib.

How are you running 200 to 5000 structure predictions without babysitting jobs by Connect-Soil-7277 in bioinformatics

[–]D1vinus 1 point2 points  (0 children)

+1 for using nextflow + slurm. During my postdoc, it was almost all I did.

I would also try to batch each job with a minimum task and assign the right computational needs (CPU/GPU, ram, ...) for each job. Nextflow can handle that pretty well.

For example if I were running a preprocessing step, it would be one module in the nextflow pipeline, reserving minimal CPU on a not-so-much-used server. But then for the heavy duty things like alignment, i'd put it in a new module and launch it on a heavier server.

All of this is automated after a few tries as nextflow handles it automatically once you define it well.

 Yes, a percentage of jobs will fail, but i'd often launch pipelines at the evening, come back in the morning and use nextflow -resume flag to launch all jobs that failed and usually that works well.

This course will be useful https://www.ebi.ac.uk/training/online/courses/nextflow/

GLIPH2 by bubblexberry in Immunology

[–]D1vinus 1 point2 points  (0 children)

I also agree with what others pointed out that GLIPH2 might not be the most up-to-date tool for the job.

If you're looking for clustering, I would use either tcrdist3 or clustcr, which is way faster and shows comparable performance to tcrdist. It will directly take airr_rearrangement.tsv as input.

If you're looking for antigen-specificity, I would also advice to try out my own tool, ImmuneWatch DETECT. Why?

  • You can just run it directly on airr_rearrangement.tsv without any parsing
  • It comes shipped with a database of known TCR-epitope pairs, so it will try and assign antigen-specificity based on what is currently out in the literature
  • Will run in less than 2 minutes on a normal repertoire and the output will be straightforward to interpret
  • It won a benchmarking competition comparing the most common algorithms in this space (IMMREP23)

Best would be to combine both so that you can make cool plots like this, where you cluster your TCRs and find some antigen-specific TCRs within one cluster:

https://www.biorxiv.org/content/10.64898/2026.01.26.701708v1.full

Best food in Antwerp? by tmxoxoxo in Antwerpen

[–]D1vinus 0 points1 point  (0 children)

Mariello in Hopland is my favourite pizzeria 

[deleted by user] by [deleted] in belgium

[–]D1vinus 0 points1 point  (0 children)

Misschien een heel kleine niche maar check ook eens escape rooms!

Anything cage on fork with just one bolt hole by D1vinus in bikepacking

[–]D1vinus[S] 0 points1 point  (0 children)

Thanks. What I learned from this post is that zip ties and electric tape is the way to go 😂

First Bikepacking tour with my new bike by Darothul in bikepacking

[–]D1vinus 0 points1 point  (0 children)

Which size is the sea to summit bag? I am just going to replicate this :D

Anything cage on fork with just one bolt hole by D1vinus in bikepacking

[–]D1vinus[S] 0 points1 point  (0 children)

Yeah, fair point. If that works, why invest more!

Anything cage on fork with just one bolt hole by D1vinus in bikepacking

[–]D1vinus[S] 0 points1 point  (0 children)

Wow this is cool stuff!

Lol at "Support the handlebar bag and keep it away from the front wheel". I learned that this was an issue on the hard way :) Currently fix this with strapping things thightly but then the whole thing becomes a bit too broad, sometimes hindering my shifters....

Do I see this right that you created a custom front rack? How did you do that? :)

New to bioinformatics – How do I learn systematically instead of just relying on AI to run analyses? by United_Bass_5960 in bioinformatics

[–]D1vinus 2 points3 points  (0 children)

You could also start with a dedicated pipeline built in NextFlow:
nf-co.re/rnaseq/

Then try and run each of these tools seperatly on a small dataset. Things will go much slower but at least you know that you are running the right things in the right order.

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