Top 40
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Transcriptomics
Formal models for compositionality, batch effects, and uncertainty in omics inference
Omics datasets with compositional structure, batch effects, and high dimensionality demand explicit uncertainty quantification.
Single-cell
Long-read and single-cell methods resolve isoforms, haplotypes, and cell identity in…
Recent long-read and single-cell studies push isoform, X-inactivation, and annotation questions to higher resolution across tissues and cohorts.
ML / AI methods
Interpretable models link omics, knowledge graphs, and drug response predictions
Foundation-model embeddings are now being paired with knowledge graphs and mechanistic priors to make biological inference interpretable.
Single-cell
Computational methods infer unmeasured features from spatial transcriptomic data
Recent preprints and published papers extend spatial inference to whole-slide reconstruction, multimodal registration, and cross-modality integration.
ML / AI methods
Joint embeddings across transcriptomic, spatial, histology, and methylation data
Recent preprints and journal papers pair histology, spatial transcriptomics, methylation, and cell-free nucleic acids in shared learned representations.