Top 40
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Transcriptomics
Graph and generative learning models decode spatial and single-cell transcriptomes
A dense batch of July 2026 publications and preprints targets resolution, annotation and integration across spatial and single-cell transcriptomics.
ML / AI methods
Multimodal deep learning predicts drug responses, interactions, and perturbation effects
Foundation models and attention architectures are now benchmarked directly against specialized drug and perturbation predictors.
ML / AI methods
Embedding pathway structure and uncertainty into omics prediction models
Small-sample, incomplete, and heterogeneous omics data are pushing prediction models toward explicit biological structure and calibrated uncertainty.
Genomics
Multiomics methods link genetic variation to gene networks and disease risk
Recent methods papers extend multiomics integration, Mendelian randomization, and GWAS power analyses using summary statistics and single-cell data.
Single-cell
Inferring gene regulatory networks and cell-cell signaling from single-cell data
Recent work adds trajectory, regulatory priors, latent TF activity, and scRNA-ATAC coupling to single-cell regulatory network inference.