Chloe Hsu
This was my academic website.
I completed my PhD at the University of California, Berkeley,
advised by Jennifer Listgarten and Moritz Hardt.
|
|
Generative models for protein structures and sequences
Chloe Hsu, Clara Fannjiang, and Jennifer Listgarten
Nature Biotechnology, 2024
paper
(Published as a primer) How can generative models be useful for protein engineering?
|
|
Learning inverse folding from millions of predicted structures
Chloe Hsu, Robert Verkuil, Jason Liu, Zeming Lin, Brian Hie, Tom Sercu, Adam Lerer*, Alexander Rives*
ICML (Outstanding Paper Runner Up Award), 2022
paper
| code
| slides
| colab notebook
Inverse folding aims to design sequences to fold into desired structures.
With 12M new predicted structures as additional training data, ESM-IF1 is more accurate at structure-based sequence design, while also generalizing to more sophisticated design tasks.
|
|
Learning protein fitness models from evolutionary and assay-labeled data
Chloe Hsu, Hunter Nisonoff, Clara Fannjiang, and Jennifer Listgarten
Nature Biotechnology, 2022
paper
| talk
| code
A simple yet highly effective hybrid approach to protein fitness
prediction.
Also a comparative analysis to highlight the importance of systematic evaluations and
sufficient baselines.
|
|
Nanopore callers for epigenetics from limited supervised data
Brian Yao, Chloe Hsu, Gal Goldner, Yael Michaeli, Yuval Ebenstein, and Jennifer Listgarten
bioRxiv, 2021
paper
Calling epigenetic modifications on nanopore sequencing platforms when the training data is incomplete.
|
|