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Variant effects

Variant effects

Created Sep 26, 2026Modified Sep 07, 2026

Predicting mutation-induced effects on fitness or pathogenicity. Add a property-specific tag only when that property is a substantive focus.

53 items with this tag.

Sep 25, 2026
Linear models remain competitive on epistasis-enriched protein fitness tests
- prediction/variant-effects
- evidence/generalization
Sep 07, 2026
Fine-tuning PLMs on rank is more effective than fine-tuning on property (regression)
Aug 25, 2026
Structural tokens improve zero-shot variant effect prediction in ESM3, but only when structures are not computationally derived
Aug 25, 2026
Zero-shot protein fitness prediction using sequence-only NNs can be improved by averaging predictions from many orthologs
- prediction/variant-effects
- inference/ensembling
Aug 19, 2026
Fine-tuned protein language models can struggle to generalize to positions absent from fine-tuning data
Aug 19, 2026
SaProt
- model-design/multimodal
- prediction/variant-effects
Jul 28, 2026
All-atom structure and affinity predictors partially generalize to point mutants
Jul 28, 2026
Zero-shot performance of PLMs, but not inverse folding models, correlates with number of homologs available for training
- prediction/variant-effects
- evidence/datasets
Jul 22, 2026
Protein property prediction using PLMs does not benefit from scale except when predicting inferring features of either structural or sparsely populated sequence families
- training/pretraining-and-scaling
- prediction/variant-effects
Jul 17, 2026
Aggregate benchmark correlations can mask weak within-category performance
- evidence/measurements
- prediction/variant-effects
Jul 17, 2026
Distinct fitness measurements of the same variants of the same protein vary wildly in Spearman
- evidence/measurements
- prediction/variant-effects
Jul 17, 2026
Language models cannot extrapolate to functional novelty or ultra-high-fitness variants
Apr 21, 2026
Changes to hydrophobicity and charge correlate with antibody escape
- prediction/variant-effects
- antibodies/recognition
Apr 21, 2026
Using evolutionary information for label smoothing during inverse folding training leads to improved fitness prediction
Apr 21, 2026
Accounting for substitution likelihood improves variant effect prediction relative to log-likelihood
- prediction/variant-effects
- evolution/selection
Apr 21, 2026
AlphaMissense
- prediction/variant-effects
- training/fine-tuning
Apr 21, 2026
Averaging logits from multiple sources can improve fitness prediction
Apr 21, 2026
EVE
- prediction/variant-effects
- evolution/selection
Apr 21, 2026
Fine-tuning base models on test cases can improve the performance of variant effect and structure prediction
Apr 21, 2026
Fitness prediction
- prediction/variant-effects
- evolution/mutation-effects
Apr 21, 2026
Half of all disease-causing missense variants due to disruption of protein stability
Apr 21, 2026
High-confidence predictions from protein language models co-cluster together in embedding space and correlate with performance on variant effect prediction tasks
Apr 21, 2026
ML models must trade off bias and variance
- prediction/variant-effects
- prediction/confidence
Apr 21, 2026
MSA-based structure prediction models can be retrained as pathogenicity prediction models by upweighting BERT losses
Apr 21, 2026
Missense mutation effects are predictive of effects of indels
- evolution/mutation-effects
- prediction/variant-effects
Apr 21, 2026
Number of sequences with 90% homology is a greater predictor of viral variant effect prediction than alignment depth
Apr 21, 2026
PLMs downweigh probability of sequences with multiple mutations
- prediction/variant-effects
- evidence/generalization
Apr 21, 2026
Precision decreases and recall increases as variant effect prediction focuses on top-performing point mutations
- prediction/variant-effects
- evidence/measurements
Apr 21, 2026
Protein language models are able to predict epistasis in a zero-shot setting following a nonlinear transform
- prediction/variant-effects
- evolution/mutation-effects
Apr 21, 2026
Protein language models are better zero-shot predictors for ranking closely related sequences than distantly related sequences
- prediction/variant-effects
- evidence/generalization
Apr 21, 2026
Protein language models make equally effective predictions when trained on individual proteins or protein families
- training/pretraining-and-scaling
- prediction/variant-effects
Apr 21, 2026
ProteinNPT
- prediction/variant-effects
- model-design/architectures
Apr 21, 2026
Residue conservation and solvent exposure data perform comparably to PLMs at some property prediction tasks
Apr 21, 2026
Sequence clustering of training data affects variant effect prediction performance by PLMs
- evidence/datasets
- prediction/variant-effects
Apr 21, 2026
Sequence homology composition can affect performance of fine-tuned protein language models for variant effect prediction
Apr 21, 2026
Sequence-based variant effect prediction methods generalize to de novo proteins
- evidence/generalization
- prediction/variant-effects
Apr 21, 2026
Sequences with lower log-likelihoods are worse for zero-shot variant effect prediction using PLMs
Apr 21, 2026
Taking the minimum logit can outperform averaging logits when ensembling models for pathogenicity prediction
Apr 21, 2026
Tranception
- prediction/variant-effects
- training/pretraining-and-scaling
Apr 21, 2026
Unbalanced composition of sequence data prevents protein fitness from being identifiable from sequence data alone
Apr 21, 2026
Variant effect prediction quality correlates with DMS prediction quality
- prediction/variant-effects
- evidence/measurements
Apr 21, 2026
Variant effect prediction with homology-aware PLMs improves with ensembling of multiple prompts
Apr 21, 2026
Biophysical models outperform linear models for stability prediction
- prediction/stability-expression
- prediction/variant-effects
Apr 21, 2026
Contrastive learning of PLM embeddings on functional annotation improves variant effect prediction and homolog detection
Apr 21, 2026
Correlation between sequence log-likelihood and variant effect prediction performance breaks down as PLMs get larger
Apr 21, 2026
Fitness prediction using inverse folding can be improved with auxiliary B-factor and SASA losses
Apr 21, 2026
GFP fitness data is best fit by simple models
- prediction/variant-effects
Apr 21, 2026
Including nonfunctional sequences during training improves prediction of negatives but not positives
- evidence/datasets
- prediction/variant-effects
Apr 21, 2026
No one-size-fits-all best approach to zero-shot or few-shot protein fitness prediction
- prediction/variant-effects
- evidence/design-validation
Apr 21, 2026
Potts models and PSSMs can model fitness landscapes
- prediction/variant-effects
- evolution/mutation-effects
Apr 21, 2026
ProteinGym
- evidence/datasets
- prediction/variant-effects
Apr 21, 2026
Weighting training sequences by fitness improves identification of other fit sequences
- evidence/datasets
- prediction/variant-effects
Apr 20, 2026
Variant effect prediction
- prediction/variant-effects

Created with Quartz v4.5.2 © 2026

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