Top 40
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Transcriptomics
Higher-order and topological views recover disease structure from multi-omic data
Spatial, isoform, and multi-omic methods now add higher-order and topological readouts of disease states beyond conventional enrichment and signatures.
ML / AI methods
Foundation models and interpretable learners predict molecular and peptide properties
Protein language models, graph encoders, and gradient-boosted trees are being benchmarked on ADMET, permeability, binding, and solubility endpoints.
Genomics
Integrated evidence tools rank genes, variants and drugs for disease
Preprints and published studies now fuse GWAS, eQTL, MAVE and in silico evidence to prioritize genes, variants and drug targets.
Single-cell
Computational models infer cell states, perturbation responses and regulatory networks
Foundation models, federated tabular learning and optimal transport methods are now applied to single-cell, spatial and bulk data across perturbation and…
Transcriptomics
Computational correction and calibration of RNA sequencing quantities
Preprints now pair RT-PCR residuals, gene-specific normalization and AnnData-native tooling with long-read benchmarking to tighten RNA-seq quantification.