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Tools & infrastructure
Error-aware low-frequency variant calling and reproducible pipelines for sequencing data
Recent preprints model background error in low-frequency cfDNA variant detection, while published workflows package modular, reproducible pipelines for genomic…
ML / AI methods
Models fuse histology, spatial transcriptomics and imaging to resolve tissue structure
Spatial omics datasets now pair histology, expression and position, and recent methods model these modalities jointly.
Transcriptomics
Graph neural networks learn cellular niches, spatial domains, and multi-omics features
Recent publications apply graph learning to spatial transcriptomics, multi-omics, nanopore methylation, and PTM site prediction.
Single-cell
Computational methods link cell identity, chromatin loops and spatial programs
Recent preprints and papers pair interpretable models with explicit validation across single-cell, spatial and bulk omics analysis.
ML / AI methods
Benchmarks Show Omics and Genomic Models Yield Unstable, Task-Dependent Performance
Recent benchmarks test whether learned omics and genomic representations generalize across modalities, tasks, and ancestry groups.