DiffPaSS – Differentiable and Scalable Pairing of Biological Sequences Using Soft Scores
Abstract
Identifying interacting sequences from two sets of potential partners has important applications in computational biology. Several methods have been developed to address this problem, applying different approximate optimization methods to different scores. We introduce DiffPaSS, a framework for flexible, fast, scalable, and hyperparameter-free optimization for pairing interacting biological sequences, which can be applied to a wide variety of scores. DiffPaSS consistently finds strong score optima, outperforming existing algorithms for optimizing the same scores.
Cite
Text
Lupo et al. "DiffPaSS – Differentiable and Scalable Pairing of Biological Sequences Using Soft Scores." ICLR 2024 Workshops: GEM, 2024.Markdown
[Lupo et al. "DiffPaSS – Differentiable and Scalable Pairing of Biological Sequences Using Soft Scores." ICLR 2024 Workshops: GEM, 2024.](https://mlanthology.org/iclrw/2024/lupo2024iclrw-diffpass/)BibTeX
@inproceedings{lupo2024iclrw-diffpass,
title = {{DiffPaSS – Differentiable and Scalable Pairing of Biological Sequences Using Soft Scores}},
author = {Lupo, Umberto and Sgarbossa, Damiano and Milighetti, Martina and Bitbol, Anne-Florence},
booktitle = {ICLR 2024 Workshops: GEM},
year = {2024},
url = {https://mlanthology.org/iclrw/2024/lupo2024iclrw-diffpass/}
}