Exploring evolution-based & -free protein language models as protein function predictors
By Min Hu, Fajie Yuan, Kevin Kaichuang Yang, Fusong Ju, Jin Su, Hui Wang, Fei Yang, Qiuyang Ding. 2022
16 citations recorded by the source corpus.
Subfields: Molecular Biology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Aurelie C. Lozano
- Zuobai Zhang
- Jian Tang
- Payel Das
- Vijil Chenthamarakshan
- Yi Zhao
- Minghao Xu
- Zhenyu Yang
Citations in the corpus
- AlphaFold2 and its applications in the fields of biology and medicine (2023, background): “Hu et al.(131) explored the utility of the Protein Language Models (PLMs) module in AF2, Evoformer, in protein function prediction, and particularly compared the performance of evolution-based & evolution-free protein language models as protein function predictors.”
- Protein Representation Learning by Geometric Structure Pretraining (2022, methodology): “We do not include MSA-based baselines, since these evolution-based methods require a lot of resources for the computation and storage of MSAs but have been shown to be inferior to ESM-1b on function prediction tasks in Hu et al. (2022).”