Top 40
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ML / AI methods
Deep and boosting models predict RNA, chromatin and gene regulatory features from omics
Recent preprints and publications apply supervised deep and boosting models to sequence, signal and expression inputs for biomolecular annotation.
Epigenomics
Sequence-to-function models decode regulatory grammar and 3D chromatin organization
Sequence-to-function models now yield interpretable regulatory rules and 3D genome predictions, extending from enhancers to cross-species Hi-C comparison.
Transcriptomics
Benchmarking ambient RNA removal and deconvolution across single-cell and spatial data
Systematic benchmarks now evaluate ambient RNA removal, deconvolution, and spatial platforms using simulations and paired donor-matched data.
Genomics
Tools for simulating and inferring population variation from haplotypes and mitogenomes
Recent preprints and one publication extend simulation, mitochondrial frequency and ancestry inference to real haplotype and reference-panel data.
ML / AI methods
Computational resources map regulatory elements and transcripts across cancer datasets
Large cancer transcriptomic and single-cell datasets now enable systematic regulatory readouts across enhancers, transposable elements, and miRNAs.