Top 40
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Transcriptomics
Learned embeddings recover spatial structure and cell states from transcriptomic data
Spatial and single-cell transcriptomics increasingly pair deep representation learning with benchmarks that test transfer across tissues and technologies.
ML / AI methods
Benchmarking computational omics methods against defined references and scenarios
Benchmarks now test perturbation, CRISPR, siRNA and synthetic-data methods against leakage-free validation, controlled simulators and explicit scenarios.
Transcriptomics
Computational frameworks for methylation, transcriptomic, and spatial omics profiling
Recent work pairs new profiling methods with benchmarks against reference data, targeting methylation, spatial, and cross-platform expression readouts.
Single-cell
Regulatory networks and morphology are used to infer single-cell state transitions
Regulatory-network and morphological readouts now serve as inferential handles on cell-state transitions beyond transcriptomics alone.
Structural bio & protein design
Molecular dynamics maps conformational landscapes and allosteric states in drug targets
Atomistic simulations with enhanced sampling now quantify allosteric, electrostatic, and ligand-binding energetics across diverse targets.