Top 40
View all ›BACKFILLED Code and industry signals are partial for backfilled days.
Rank 1
ML / AI methods
Deep learning aligns, segments and decodes spatial tissue and cellular imaging data
Multiplexed imaging, spatial omics and cryo-ET now pair self-supervised and graph-based models with sparse labels and batch-effect correction.
8 preprints · 7 published · ↑ 2.4× vs 4-wk avg
Rank 2 ML / AI methods
Pretrained protein language model embeddings drive task-specific function predictors
Recent work applies pretrained PLM embeddings to tasks from E3 ligase prediction to TCR design and lipid-binding classification.
4 preprints · 12 published · ↑ 2.5× vs 4-wk avg
Rank 3 Single-cell
Statistical methods test gene expression and regulation along single-cell trajectories
Pseudotime-resolved inference now pairs trajectory and covariate structure with calibrated testing at cell-state resolution across recent preprints and…
3 preprints · 11 published · ↑ 2.3× vs 4-wk avg
Rank 4 ML / AI methods
Learned fusion of histology, omics and cfDNA features for cancer prediction
Integrative learning models now extend beyond bulk omics to cell-free DNA, spatial transcriptomics and calibrated spatial tumor simulation.
4 preprints · 9 published · ↑ 2.1× vs 4-wk avg
Rank 5 Single-cell
Generative models separate cell states and transfer labels across single-cell datasets
Single-cell and spatial omics datasets now demand interpretable models that separate biological factors from batch, perturbation, and cell-cycle variation.
5 preprints · 8 published · ↑ 2.1× vs 4-wk avg
Rank 6 Graph networks model cross-omics feature dependencies for patient stratification↑ 2.0×ML / AI methodsRank 7 Graph neural networks fuse structure and sequence embeddings for biological prediction↑ 1.7×ML / AI methodsRank 8 ML models prioritize drug synergy, repurposing and toxicity from multimodal data↑ 1.7×ML / AI methodsRank 9 Deep models assign nanopore current traces to protein capture phases and sequencing…↑ 1.6×ML / AI methodsRank 10 WGS variant calling benchmarks and new SV, CNV and de novo callers refine detection↑ 1.6×GenomicsRank 11 Deep learning models predict regulatory states from DNA sequence and chromatin context↑ 1.6×EpigenomicsRank 12 Ordering spatial transcriptomic snapshots in time to infer cell fate trajectories↑ 1.6×TranscriptomicsRank 13 Packaging sequence-analysis steps into reproducible, runnable software tools↑ 1.6×Tools & infrastructureRank 14 SE(3)-equivariant diffusion now generates conformational ensembles and trajectoriesStructural bio & protein designRank 15 Generative models now judged by synthesizability and confirmed-active benchmarksStructural bio & protein designRank 16 Interpretable learning models target microbial interactions and resistance phenotypesML / AI methodsRank 17 Inferring regulatory and splicing activity from MPRA, knockdown and single-cell readoutsEpigenomicsRank 18 Structure-aware models predict complex binding; benchmarks expose scorer biasStructural bio & protein designRank 19 Computational tools infer kinetic and surrogate parameters for biological modelsSystems biologyRank 20 Computational tools refine microbial profiling from sequencing depth to reference…Tools & infrastructure
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Rank 21 Automated mining and reconciliation of public biomedical data into queryable networksTools & infrastructureRank 22 Open-source tools for interactive, reproducible omics and metagenomic data explorationTools & infrastructureRank 23 Benchmarks calibrate nanopore and cfDNA readouts against orthogonal reference sitesEpigenomicsRank 24 Post-GWAS inference adapts to relatedness, pathway specificity and gene rankingGenomicsRank 25 Faster, leaner algorithms for alignment, motif scoring, genome size and read processingTools & infrastructureRank 26 Benchmarking and scaling computational phage-host assignment across viral genomesTools & infrastructureRank 27 Usable software tools now deliver spatial, breeding, and metabolic modeling methodsTools & infrastructureRank 28 Epiallele-resolved methylation meets long-read and pangenome genomicsGenomicsRank 29 Automated preparation links cofolding predictions to MD of protein and lipid systemsStructural bio & protein designRank 30 Sparse and learned models move genetic association beyond single-locus additive effectsGenomicsRank 31 Generative and docking methods prioritize candidate molecules for experimental testingStructural bio & protein designRank 32 Mobile element exchange networks and plasmid tools resolve bacterial gene variationGenomicsRank 33 Computational encoding of PTM chemistry and coexisting modifications in MS proteomicsProteomicsRank 34 Simulation models link dosing and resource supply to resistance and colonizationSystems biologyRank 35 Simulations and models map sequence-encoded allosteric control in RNA systemsStructural bio & protein designRank 36 Pretrained sequence models target genome annotation and transposable element typingGenomicsRank 37 ML potentials, RNA ensemble validation, and AI structure prediction teaching resourcesStructural bio & protein designRank 38 New consistent tree methods for gene, species and network phylogeniesGenomicsRank 39 Reference genomes and genotyping resources for annelid, cricket, scallop and tunicate…GenomicsRank 40 Computational inference of microbial enzyme and metabolic capabilities across genomesMetabolomics