Top 40
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ML / AI methods
Learned models couple histology, transcriptomics, and regulatory networks in omics
Recent preprints extend graph, foundation, and causal models to spatial, single-cell, and multi-omic data, with benchmarks testing whether gains hold.
Single-cell
Computational methods correct spatial RNA leakage and infer single-cell states
Recent preprints and publications pair spatial decontamination, uncertainty-aware modeling and single-cell network inference with rigorous benchmarking.
Structural bio & protein design
Computational tools target model selection, cryo-EM building, and fold switching
Structure predictors and cryo-EM models now face systematic evaluation of sampling, selection, and confidence discordance.
Structural bio & protein design
Learned models predict protein-ligand, protein-RNA, and disordered-region binding sites
Recent preprints and papers pair topological, geometric, and state-space learning with protein structure and dynamics to predict binding behavior.
Genomics
Reference-anchored benchmarks refine variant calling in hard-to-map and clinical regions
Pangenome and IUPAC-consensus references now show measurable recall and detection gains in difficult genomic regions, motivating reference-anchored variant…