@caina89
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Our new preprint “Learning lifetime disease liability reveals and removes genetic confounding in electronic health records” is now online! Link to paper: medrxiv.org/cgi/content/shor… This work is led by my postdoc @diyazheng_ and it’s our first project at @ETH_BSSE :)
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Na Cai retweeted
Please help spread the word! We are recruiting multiple Postdoctoral Fellows as part of the recently launched Bakar Computational Biomedicine Initiative (BCBI) at UC Berkeley and UCSF.
BCBI website: bcbi.berkeley.edu/
Apply by Nov 1, 2026: berkeley.infoready4.com/#fre…
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Na Cai retweeted
We are thrilled to share that our GPN-Star manuscript is now published and freely available:
doi.org/10.1038/s41586-026-1…
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Na Cai retweeted
CIGMA is out in Nature — A linear mixed model to unbiasedly characterize cell-type-specific eQTLs. Work advised by @andywdahl and a lot of help from @xinpei_w
nature.com/articles/s41586-0…
Na Cai retweeted
New preprint on a surprising question - with a pangenome reference, *what is a genetic variant?*
biorxiv.org/content/10.1101/…
With Pouria Salehi Nowbandani, Shenghan Zhang, Haoyang Hu, and Heng Li @lh3lh3
Na Cai retweeted
Another incredible genomics paper from Po-Ru Loh’s team just dropped in Nature.
The team analyzed whole genome sequence (WGS) data of 900,000 individuals from the UK Biobank and All of Us and report fascinating insights on short tandem repeat (STR) mutations in the human genome.
At the core of the paper is the authors’ creative methodologies to overcome the challenges involved in using short read WGS data of unrelated individuals to study germline and somatic repeat expansions.
Must read for anyone interested in repeat mutations and genetics of repeat expansion disorders.
Hujoel et al. Nature 2026
nature.com/articles/s41586-0…
Na Cai retweeted
I am thrilled to share that UC Berkeley and UCSF have launched a joint initiative in Computational Biomedicine!
cdss.berkeley.edu/news/uc-be…
We will soon be recruiting new faculty and postdoctoral fellows. Please repost to help spread the word.
Na Cai retweeted
Happy to share our new work: "scEPS integrates genetic and single-cell disease atlas data to provide granular mechanistic insights into complex human diseases"! 🧬🔬
medrxiv.org/content/10.64898…
Na Cai retweeted
Want to do a 𝐩𝐨𝐬𝐭𝐝𝐨𝐜 in my group at 𝐄𝐓𝐇 𝐙𝐮𝐫𝐢𝐜𝐡?
Check out our new position on "Multimodal reasoning models for oncology"
which is centered around a new collab between our lab and kaiko . ai
In addition, our group is engaged with the ETH AI Center and SwissAI projects where we have access to large-scale GPU ressources. Links in comment.
Na Cai retweeted
Please check out our forthcoming ICML paper on learning the BCR affinity maturation process, with applications in variant effect prediction and antibody design.
Antibody LMs learn what looks antibody-like, but not how selection turns naive germline antibodies into strong binders.
@aakarshv1 and I are excited to share CoSiNE, a model that learns this germline-to-mature process for variant effect prediction and antibody design. (1/8)
Na Cai retweeted
A paper in Nature presents molecular clocks that can provide accurate estimates of both molecular age and lifespan across multiple mammalian species and tissue types. This framework may aid the development of targeted interventions to improve longevity. go.nature.com/3PHOtsa
ALT This is figure 5, which shows ageing-related diseases in mammals exhibit shared transcriptomic hallmarks of mortality.
Na Cai retweeted
🧠Grant from #HortenHealthFoundation powers #AI-based research in computational genetics led by Na Cai @caina89 @ETH_en to uncover molecular subtypes of major depressive disorder 👉🏾tinyurl.com/2wyrjxcs
Na Cai retweeted
Why do pathogenic variants in the same gene lead to different neurodevelopmental outcomes?
Our Trends in Genetics review discusses how variant effects, genetic background, environment, and developmental noise may all contribute.
cell.com/trends/genetics/abs…
authors.elsevier.com/a/1mxFv…
Na Cai retweeted
[Preprint alert] Process reward agents (PRA)
Why is it relatively easy to get LLMs to produce strong reasoning traces in math/code…
but much harder in application domains like health?
Check out our new paper & 🧵below:
Na Cai retweeted
A little widget to play around with the various inputs and outputs that go into soft money research lab finances on a 10-year outlook.
Na Cai retweeted
Now out in @GenomeBiology!
HistoGWAS combines histology foundation models, statistical genetics and generative AI to characterize variant effects on tissue morphology, enabling genetic analysis at the tissue scale.
Led by @skc_2017
@HelmholtzMunich @PioneerCampus
📢 Call for submissions:
The RECOMB-Genetics satellite workshop will take place in Thessaloniki, Greece 🇬🇷 on May 25, 2026, just before the RECOMB conference (May 26–29) @RECOMBconf
📅 Submission deadline: April 2 (AoE)
👉 recomb.org/recomb2026/recomb…
Submit your work and join us!
Na Cai retweeted
Final days for a chance to present your research at the #RECOMB2026 Satellite Meetings ⏳
Submission link: easychair.org/conferences/?c…
Na Cai retweeted
New work from our group developing a method to estimate the molecular heritability of longitudinal traits (e.g. disease onset, progression, or death). Many traits appear to be a genetic mixture of onset/liability and progression components. See Kodi's thread for more:
Excited to share our preprint introducing COXMM! COXMM is a Cox proportional hazard mixed model for estimating the heritability of time-to-event (TTE)/longitudinal traits. 🧵1/10
Work with @SashaGusevPosts and @sr_sankararaman.
doi.org/10.64898/2026.02.16.…
Na Cai retweeted
Submission to the Posters Track are now open!
📌 Early submission deadline: 20 March 2026
Visit recomb.org/recomb2026/call_f… for details 📝
#RECOMB2026 #submissions #CallForPosters
