Nathan's Substack
Nathan C. Frey, Amy Lu, Eric Dai, Dan Berenberg, Aya Abdelsalam Ismail, Isabelle Heifetz Ament, Frédéric DreyerI write about biotech and machine learning
| Platform |  | Pricing | Only free issues | Publishes | Infrequently |
|---|---|---|---|---|---|
| Issues | 20 | Subscribers | Read | ncfrey.substack.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
Reading Between the Isoforms: Interpretable Machine Learning Meets Long-Read RNA-Seq for Biomarker Discovery
Isabelle is a PhD student at my alma mater, the University of Pennsylvania, in the Lin Lab at the Children’s Hospital of Philadelphia (CHOP). The Lin Lab developed TEQUILA-seq, a low-cost method for long-read RNA sequencing. Isabelle’s PhD ...
The Nuances of Antibody Structure Prediction
This is a guest post by Frédéric Dreyer, AI/ML research scientist, protein designer, recovering high-energy physicist, and my go-to authority on anything and everything related to antibody structure prediction and de novo design. In the cur...
Publishing and communicating research in AI/ML is fundamentally broken
The premier venues for publishing and communicating research in AI and ML, the conference main tracks (NeurIPS, ICLR, ICML, etc.) are fundamentally broken.
Getting started in BioML Research & Engineering
Of all the blog posts I’ve written, Getting Started in Materials Informatics has probably generated the most positive feedback and engagement. With the incredible growth in BioML over the past few years, and the fact that hiring is one of, ...
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Authors
The writers behind this newsletter.
CTO & Co-Founder, Coefficient Bio | Ex-Prescient Design • Genentech | Scientific advisor to Atomscale and Guide Labs
bio x tech per vita ad astra
comp [sci|bio]
I am an ML Research Scientist that mainly works on interpretability
I'm a PhD Candidate at the University of Pennsylvania/Children's Hospital of Philadelphia mapping the human genome via long-read RNA-seq method development.
Machine learning researcher at Prescient Design/Genentech, interested in large molecule drug discovery.
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