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Keyword: model regularization ×Clear all

2 claims from 1 paper

1. Biochemistry, Genetics and Molecular Biology › Genomics and Rare Diseases

   Structure-informed protein language models are robust predictors for variant effects

   Sun and Shen · Human Genetics · 2024

   The authors add protein structure context to sequence-only protein language models during training, and report that these models predict variant effects robustly, even when smaller and trained on less data.

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   1. UncheckedStructure-informed protein language models, though smaller and trained on less data, were top performers on mutation-scanning benchmarks against competing methods.“Numerical results over deep mutagenesis scanning benchmarks show that our SI-pLMs, even when using smaller models and less data, are robustly top performers against competing methods including other pLMs, which shows that introducing biological context can be more effective at capturing fitness lan…”
   2. Unchecked“Case studies reveal that, compared to sequence-only pLMs, SI-pLMs can be better at capturing fitness landscape because (a) learned embeddings of low/high-fitness sequences can be more separable and (b) learned amino-acid distributions of functionally and evo…