Machine learning for biology
Alphafold, connectomics, and other applications
2025-01-01 — 2025-01-01
Wherein Approaches for Expediting Cellular Experiments and Enhancing Dataset Quality Are Outlined, With Emphasis on Shortening Experiment Cycles and Collecting Higher-Fidelity Cell-Level Measurements.
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Levers for Biological Progress - by Niko McCarty
In order for 50-100 years of biological progress to be condensed into 5-10 years of work, we’ll need to get much better at running experiments quickly and also collecting higher-quality datasets. This essay focuses on how we might do both, specifically for the cell. Though my focus in this essay is narrow — I don’t discuss bottlenecks in clinical trials, human disease, or animal testing — I hope others will take on these challenges in similar essays.