Top 40
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ML / AI methods
Encoding biological knowledge into compact sequence models for genomic and protein tasks
Alignment-free k-mer, taxonomy-guided, and structure-aware representations offer compact alternatives to alignment-based sequence analysis pipelines.
Genomics
Computational methods link variant effects to gene-level and trait-level inference
Variant-level evidence is being converted into gene-level and trait-level inference, with calibration and ancestry performance now assessed directly.
Single-cell
Computational methods infer spatial tissue organization from spatial transcriptomics data
Recent preprints extend spatial marker detection, domain discovery, slice alignment, and cell-trait mapping to imaging and spatial transcriptomics data.
Structural bio & protein design
Learned protein and peptide representations drive binding prediction and design
Recent preprints and papers test protein language model embeddings directly against binding, viability and design tasks.
Structural bio & protein design
Learned models predict biomolecular evolution, dynamics and variant effects
Zero-shot sequence models predict additive mutations well but fail under strong epistasis, constraining variant-effect prediction claims.