Top 40
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ML / AI methods
Learned models extract more biology from sequence and read data across genomics
Deep, foundation, and Bayesian models are now applied to genomic, microbiome, and viral prediction tasks with explicit uncertainty handling.
ML / AI methods
Multimodal and interpretable models predict drug, protein, and RNA interactions
Interpretable, multimodal architectures now target drug-target, drug-drug, PROTAC degradation, and kinase variant prediction in one August 2026 batch.
Structural bio & protein design
Deep learning models predict protein folds, binding affinities, and designed backbones
Recent preprints and journal papers apply co-folding foundation models and protein language models to enzyme specificity, binding affinity, and design.
Tools & infrastructure
Automated pipelines and browser tools streamline omics curation and analysis
Five August 2026 items pair automated curation, selection, and sparse-learning workflows with browser or GUI interfaces for routine omics analysis.
Systems biology
Spatial and time-resolved omics methods link gene regulation to disease biology
New methods model spatial, temporal, and genetic variation to resolve disease-relevant structure in omics and population data.