Nathan Skene
@n_skene
Neurogenomics lab @UKDRI at Imperial College. Integrating single-cell data with GWAS to gain insight into brain function and disease
Want to know which cell types underlie complex brain traits, including PD, Schiz, Alzh and BMI? We wanted to know the answer and that has lead to our latest preprint (bit.ly/2UbI8mk) in a fun collaboration between myself, @JulienBryois, Pat Sullivan and @HjerlingLeffler
Short Sleep Variants Do Not Replicate In March Kristjan Moore from deCODE genetics emailed me urging me to stop working on short sleep. I read paper in question since Jan, but was still hoping/coping that maybe NPSR1 variant (not included in the paper) would replicate.
Probably the most promising use of proteomics in drug development is creating signatures that act as surrogates for hard endpoints in early phase trials. In a MASH trial, semaglutide showed dose-dependent effects on serum proteomic signatures of liver histology mirroring actual…
I'm excited to share work on a research direction my team has been advancing: connecting machine learning derived genetic variant embeddings to downstream tasks in human genetics. This work was led by the amazing @divyanshi91! biorxiv.org/content/10.110…
While UK Biobank enabled access to population-based proteomics at scale, most omics studies in disease-focused cohorts still suffer from small sample sizes. The Global Neurodegeneration Proteomics Consortium brought together 35,000 serum, plasma, and CSF samples from…
IMO, medium scale combinatorial regulator perturb expts with diverse measurable stoichiometry are going to be far more informative to learn causal models of cis-trans regulation than genome scale single gene knockouts. Hope we get more of these kinds of datasets at scale. 1/
reprogramming cells with transcription factors is our most expressive tool for engineering cell state traditionally, we found TFs by ~guesswork @icmlconf we're sharing @newlimit's SOTA AI models that can design reprogramming payloads by building on molecular foundation models
Excited to share a milestone published in @NatureMedicine from our decade-long effort to build The Human Phenotype Project, a unique longitudinal cohort with unmatched depth of clinical and multi-omic profiling, enabling truly predictive, personalized medicine. Led together with…
💡 Apparently, if you throw 10+ proteins into each AlphaFold3 run, you get whole interactomes on the house😂🧬 “Pooled” folding reduces # jobs 100×, halves runtime, and even spots novel PPIs
🧠🔬 A new microscope, ExA-SPIM, lets researchers zoom from molecules to whole brains, no slicing required. By combining tissue expansion with high-speed imaging, it captures stunning detail across entire mouse brains and even human samples. elifesciences.org/articles/91979…
The discussion around virtual cell models has primarily focused on algorithms and metrics. What about the training data? Is scRNA-seq good enough? A key challenge is distinguishing direct vs indirect effects on gene expression. 1/5
1/ How to keep, and profit from, British Antarctica It's eight times the size of Great Britain and is rich in resources – oil and gas, plus (judging by the geology) plenty of rare earths. The jewel is the peninsula: comparatively mineable, but already contested. A proposal🧵
The very first task I usually give new pretraining people is to run a tiny transformer, profile it, and understand it deeply. I wrote up a small tutorial covering this exact workflow. I talk about how to measure GPU perf, how to estimate tensor core speedup, etc. Take a look:
A beautiful paper that goes through Diffusion step by step, explaining the entire math of it from the beginning.
Key numbers in cell biology Having a sense of scale helps to think more rigorously and realistically about biological systems.
Gene therapy cures genetic deafness for the first time - in kids AND adults. One injection restored hearing in 10 people aged 1.5 to 24 years, reports @NatureMedicine Here's how 🧵
scRNAseq cell type annotation is notoriously messy. Despite so many algorithms, most researchers still rely on manual annotations using marker genes In a new preprint accepted at ICML GenAI Bio Workshop, we ask if reasoning LLMs (DeepSeek-R1) can help with cell type annotation🧵
Ah here is the new argument. Negative criticism of "virtual cells" is apparently stupid cuz nothing works the first time, it can take 26 years to solve hard scientific problems & science is hard. 1/
This week in biotechnology: 1. There is a lot of skepticism about virtual cells. I don't think negative criticism is worthwhile, in part, because the first version of everything tends to be bad. Also, AlphaFold2 came out a full 26 years after the CASP competition first began!…
My rationale was the quality of our MP's had deteriorated dramatically since the days when Labour & Conservatives could field political giants like Dennis Healey (Beachmaster at Anzio) or Airey Neave (escaped from Colditz & Prosecutor at Nuremberg ) We simply needed better people
New from the Rouhanifard Lab! What if we could sort single cells based on whether a specific gene was actively being transcribed—and then ask what drives that burst? Introducing: NuclampFISH
Another plasmid I am excited about offering is this fully open source Taq polymerase expression circuit. Inducible via lactose or IPTG. Ampicillin selected. Born free. You can make your own polymerase and purification is as easy as boiling water and centrifuging. Coming soon!
Scihub stopped uploading new articles. SciDB is a continuing effort which has the entire scihub collection AND new papers. annas-archive.org/scidb