Top 40
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ML / AI methods
External biological knowledge encoded as structural priors in deep prediction models
Recent preprints and Bioinformatics papers encode ontology, marker, and pathway knowledge as inductive structure in omics prediction.
Transcriptomics
Deep learning models integrate histology and spatial omics to resolve tissue niches
Graph and foundation models now link histology, spatial transcriptomics and proteomics across scales in recent preprints and publications.
Single-cell
New computational tools for single-cell and spatial transcriptomics analysis
Recent preprints and papers add scalable tools for atlas construction, label transfer, and spatial analysis of single-cell data.
ML / AI methods
Protein language model embeddings are probed for encoded structure and function
Recent preprints and publications test what pretrained sequence and structure embeddings encode, extending them to interaction, drug, and variant tasks.
Structural bio & protein design
Hybrid and calibrated learned models predict variant energetics and fold-switching
Recent preprints and publications recalibrate protein language and structure models against stability, binding, and fold-switching benchmarks.