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Mar 1, 2024 · This paper extends data augmentation techniques previously used for images and texts to proteins and then benchmarks these techniques on a variety of protein- ...
Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions · no code implementations • 1 Mar 2024 • Rui Sun, Lirong Wu ...
Augmentation is an effective alternative to utilize the small amount of labeled protein data. However, most of the existing work focuses on design-ing...
Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions · Rui Sun, Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li.
Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions · no code implementations • 1 Mar 2024 • Rui Sun, Lirong Wu ...
Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions. R Sun, L Wu, H Lin, Y Huang, SZ Li. arXiv preprint arXiv ...
Sep 28, 2020 · In this paper, we empirically explore a set of simple string manipulations, which we use to augment protein sequence data when fine-tuning semi-supervised ...
Missing: Enhancing | Show results with:Enhancing
Jul 2, 2024 · In this work, we introduce FSFP, a training strategy that can effectively optimize protein language models under extreme data scarcity for fitness prediction.
Missing: Augmentation: | Show results with:Augmentation:
This review provides a framework to understand how these tools fit into the overall process of de novo protein design.
Oct 18, 2024 · We assess the proposed approach using three benchmarks comprising over 300 deep mutational scanning assays. The prediction results showcase ...