Dhuvi Karthikeyan

Artificial intelligence could end disease, lead to "radical abundance," Google DeepMind CEO Demis Hassabis says At Google DeepMind, researchers are chasing what's called artificial general intelligence: a silicon intellect as versatile as a human's, but with superhuman speed and knowledge.

Today’s news about Joe Biden makes it almost difficult not to reflect on the unrealistic promises from AI leaders who claim AI could end disease and usher in radical abundance. Disease will persist. AI is a tool, not a cure-all. People deserve truth, not hype.

www.cbsnews.com/amp/news/art...

NSF slashes number of ‘rotators’ and well-paid managers as part of restructuring Smaller future budgets will require fewer people, NSF official tells staff

NSF to ONLY fund research in five areas: artificial intelligence, quantum information science, biotechnology, nuclear energy, and translational science. Can this be happening?

www.science.org/content/arti...

what do you teach at the first-year graduate course on machine learning, in this era of LLM and large-scale compute? here's my experiment on answering this question: let's teach everything that admits SGD and that is not LLM, and ask students to read old papers.

We hadn’t won World War II by May 8th. I know because my family and I were still in an internment camp in Tule Lake, California.

Your immune system gradually loses it top team players when we get older 👱➡️👵
Our study in @ebiomedicine.bsky.social investigates how long good immune cells stay around – a 🧵⬇️ go.unimelb.edu.au/4sep
@katherinekedz.bsky.social @thedohertyinst.bsky.social #Influenza #AgingResearch #Immunity #TCR

My PhD student's NSF grant was terminated today. Her dissertation investigates why air pollution monitoring, metrics, and regulations don't properly capture the harms experienced by marginalized communities--esp in the most polluted Detroit neighborhoods. She and I are happy to talk with press etc.

I am so excited to share that our new paper is out!

A model of intratumor and interpatient heterogeneity explains clinical trials of curative combination therapy for lymphoma

Out in Blood Cancer Discovery
doi.org/10.1158/2643-3230.BCD-24-0230

#mathonc #lymsm #BloodCancer
1/n

nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework Author summary We have created nf-core/airrflow, a workflow to help researchers study the immune system in healthy and disease states, such as infections, autoimmunity, and cancer. The adaptive immune...

Do you analyze large BCR and TCR sequencing datasets?

Answer our survey for improving nf-core/airrflow, a Nextflow pipeline to analyze bulk and single-cell AIRRseq data (doi.org/10.1371/jour...). We’re interested in your opinion on useful new features!

yalesurvey.ca1.qualtrics.com/jfe/form/SV_...

HHS's Office of Long COVID Research and Practice has been DOGEd. Closing this week.

We @prescientdesign.bsky.social Genentech pre-printed our "Lab-in-the-loop for therapeutic antibody design." We built a general ML system to accelerate molecule design for challenging, therapeutically relevant targets.

www.biorxiv.org/content/10.1...

You in the Triangle area and thinking about standing up for science? Come to my beloved 2nd workplace and make a sign 😊🍻 supplies provided!

You can leave a sign w me and i can bring it up to DC!

@standupforscience.bsky.social

Dear TCR researchers of #immunosky, you may be interested to know that our tool Stitchr - for the automated production of full-length T cell receptor sequences - has just had a nice little update:

jamieheather.github.io/stitchr/

list of banned keywords

🚨BREAKING. From a program officer at the National Science Foundation, a list of keywords that can cause a grant to be pulled. I will be sharing screenshots of these keywords along with a decision tree. Please share widely. This is a crisis for academic freedom & science.

Arguably well*

Musks method of ruthlessly enforcing efficiency by removing things and adding them back if the system breaks has worked well for pruning complexity of products, pipelines and entire companies. But applying this methodology to govt is dangerous and will result in greater harm to the American people

Tagging in @pranam.bsky.social

An intranasal, NLC-delivered self-amplifying RNA vaccine establishes protective immunity against pre-pandemic H5N1 and H7N9 influenza Seasonal and pandemic influenzas are continuous threats to human health, requiring rapid development of vaccines to multiple evolving viral strains. New RNA vaccine technologies have the adaptability ...

Good combo! A nasal vaccine with self-amplifying RNA (much less dose required for v potent immune response), complete protection effective vs both H5N1 and H7N9 viruses in experimental models www.biorxiv.org/content/10.1...

Ahahaha I think my brain autocorrected LLM to pLM and selectively dropped for natural language when I saw your skeet. Still a cool approach if you would like to be the first to show that it works and is useful for natural language tasks 😇

Aggregating Residue-Level Protein Language Model Embeddings with Optimal Transport Protein language models (PLMs) have emerged as powerful approaches for mapping protein sequences into embeddings suitable for various applications. As protein representation schemes, PLMs generate per...

www.biorxiv.org/content/10.1...

@rohitsingh8080.bsky.social and co have a really cool paper out on optimal transport for pooling embeddings for pLMs. Worth checking out forsure

On the merits of reading papers, attending conferences, preprinting manuscripts… Overseen at the Library of Congress.

Unsure if people on bsky are aware of o3s existence. But if anyone wants to talk I’ve been itching all day

Intuition behind why two-point statistics might provide an easier path to generalization

How to learn generalizable rules across complex sequence-function maps? 💡In our new preprint we propose a framework for learning two-point statistics and use it to discover biophysical rules of TCR co-specificity that generalize to unseen ligands ! ✨ arxiv.org/abs/2412.13722

Decrease in conformational entropy of an antibody between germline/naive sequence (left, green) and affinity-matured sequence (yellow, right)

2D free energy landscape before and after affinity maturation. Features are sin/cos of CDRH3 backbone dihedrals

Ideal test is antibody CDRH3s which often conformationally rigidify during affinity maturation. MSAs only report inter-species evolution, not intra-species maturation, so existing methods fail. Pics from doi.org/10.3389/fimmu.2018.03065 & doi.org/10.3389/fmolb.2020.00182

Huge fan of SEDD for DNA sequences! Congratulations again on a well thought out and well executed paper :)

Given the subtext here I wouldn’t be surprised if both X and Bsky develop extremely close but distinct niches: the former to blast information and reach broader audiences, and the latter as a place of discourse with members of a particular community.

🧙🪄Summoning Alex to 💙🦋 so the Bio x ML community can celebrate ESM-C with him on here as well

Also worth checking out:

academic.oup.com/bioinformati...

TLDR: performance gains from tokenization depend largely on dataset composition and specific task (complexity?).

My usual go to is VDJdb. Set antigen species to human, minimal confidence score to 3, and paired A+B. It's not perfect, but it filters out most of the cruft.

There's also a new DB called TRAIT which has a nice pack of TCRs that are being/have been trialed, which are mostly against human epitopes.