Top 40
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Single-cell
Learned representations and label-efficient models for single-cell imaging and omics
Imaging and single-cell omics increasingly rely on learned models, and label-efficient, self-supervised tools are emerging to reduce annotation burden.
ML / AI methods
Machine learning models predict immunogenicity of neoantigens and tumor epitopes
Recent tools pair omics-derived tumor antigen discovery with learned immunogenicity models, targeting neoepitope selection for vaccines and immunotherapy.
Tools & infrastructure
Large-scale genome and metagenome mining links sequence content to microbial traits
Expanding genome and metagenome collections now allow specific trait classes to be assigned from broad microbial sampling.
ML / AI methods
Pretrained sequence models tackle resistance, interactions and mRNA design
Recent preprints apply genomic, mRNA and protein language models to resistance, interaction and zoonotic surveillance tasks.
Single-cell
Foundation and graph models for spatial and single-cell transcriptomic representations
Recent preprints pair spatial and single-cell foundation models with scrutiny of benchmark sampling biases.