1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2025★ 1 cited
Overconfident Oracles: Limitations of In Silico Sequence Design Benchmarking
Shikha Surana, Nathan Grinsztajn, Timothy Atkinson +2
Machine learning methods can automate the in silico design of biological sequences, aiming to reduce costs and accelerate medical research. Given the limited access to wet labs, in…
cs.LG2024
Metalic: Meta-Learning In-Context with Protein Language Models
Jacob Beck, Shikha Surana, Manus McAuliffe +4
Predicting the biophysical and functional properties of proteins is essential for in silico protein design. Machine learning has emerged as a promising technique for such predictio…