Top 40
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Rank 1
Single-cell
Models infer regulatory and temporal dynamics from single-cell transcriptomes
Single-cell snapshots are now analyzed with explicit dynamical, causal, and perturbation-aware models rather than descriptive visualization alone.
8 preprints · 1 published · ↑ 2.7× vs 4-wk avg
Rank 2 Genomics
New tools resolve chromatin structure, haplotypes, and isoform-level splicing
Long-read sequencing and multi-omics integration now yield haplotype-resolved, near-complete genomes and isoform-level readouts in reproducible form.
3 preprints · 3 published · ↑ 2.3× vs 4-wk avg
Rank 3 Epigenomics
Sequence models map motifs, nucleosomes and CpG methylation across chromatin
Deep learning and motif-based models now predict chromatin accessibility, enhancers and methylation directly from DNA sequence.
5 preprints · 2 published · ↑ 2.4× vs 4-wk avg
Rank 4 Structural bio & protein design
Sequence-based deep learning predicts protein binding, interactions, and complex structure
Recent preprints and publications apply protein language model embeddings to binding affinity, epitopes, and structure reliability assessment from sequence.
4 preprints · 5 published · ↑ 2.1× vs 4-wk avg
Rank 5 Systems biology
Sampling frames constrain what pathogen inference can recover from surveillance data
Recent work pairs transmission models, genomic, wastewater and serological data to infer infection status from distinct sampling frames.
1 preprint · 4 published · ↑ 2.1× vs 4-wk avg
Rank 6 Learned and calibrated scores prioritize noncoding variants and transcript isoforms↑ 2.1×GenomicsRank 7 Microbial multi-omics and proteome annotation link taxa to host disease phenotypes↑ 2.0×Systems biologyRank 8 Optimal transport and graph geometry align unpaired omics and imaging modalities↑ 1.7×ML / AI methodsRank 9 Computational methods for denoising, imputing, and mapping single-cell transcriptomic data↑ 1.7×Single-cellRank 10 Deep learning models now predict genomic variant effects, mutation rates and splicing↑ 1.6×GenomicsRank 11 Single-cell foundation models gain spatial, graph, and chromatin context for prediction↑ 1.5×ML / AI methodsRank 12 MD simulations show α1-antitrypsin droplets hardening into β-sheet assemblies↑ 1.5×Structural bio & protein designRank 13 Ligands and mutations reshape dynamics of disordered and allosteric proteins↑ 1.5×Structural bio & protein designRank 14 Compressed indexes and banded alignment cut memory cost in sequence analysisTools & infrastructureRank 15 Null GWAS test bias, expression-noise QTLs and plasma metabolite causal mappingGenomicsRank 16 Computational inference of cell identity and spatial organization from transcriptomic dataTools & infrastructureRank 17 Graph and latent models of brain connectivity from EEG, SEEG, fMRI and connectomesML / AI methodsRank 18 Deep learning for segmenting, detecting, and quantifying structures in microscopy imagesML / AI methodsRank 19 Reproducible R and Nextflow pipelines for spatial, multi-omics, and network-based analysesTools & infrastructureRank 20 Topology and higher-order complexes are redefining how brain network structure is…Systems biology
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Rank 21 Sequence models conditioned on evolutionary and structural context guide protein designStructural bio & protein designRank 22 New preprints advance haplotype, lineage and methylation analysis on genomic referencesGenomicsRank 23 Tools for nanopore methylation motifs, microbial SNP ranking and metagenomic profilingTools & infrastructureRank 24 Sequence models for peptide properties, antimicrobials and compound-protein bindingML / AI methodsRank 25 Learned interaction and noise structure in high-dimensional omics regression and reductionML / AI methodsRank 26 Multi-omics and imaging data are mined to prioritize cancer target candidatesTools & infrastructureRank 27 Inferring network topology from microbial gene transfer and amplicon sequence dataGenomicsRank 28 Regime boundaries in bioelectric, aggregation, and mutation-driven aging modelsSystems biologyRank 29 Faster Fragment Docking, MD, and ML Potentials for Binding Mode PredictionStructural bio & protein designRank 30 Graph neural networks with multimodal fusion predict diverse drug-discovery endpointsML / AI methodsRank 31 Benchmarked computational workflows and pooled IP-MS advance proteomics inferenceMetabolomicsRank 32 Pretrained embeddings fused with deep predictors for protein and RNA site predictionML / AI methodsRank 33 Benchmarking and alignment design shape phylogenetic inference accuracyGenomicsRank 34 Integrating heterogeneous biological data to constrain predictive modelsSystems biologyRank 35 Context-conditioned generators design molecules, peptides, and cell morphology profilesStructural bio & protein designRank 36 Allosteric networks mediate ligand recognition in laccase and p53 Y220C stabilizersStructural bio & protein designRank 37 Genome-wide inference of duplication history, chromosome fusion and hybrid couplingGenomicsRank 38 Neural models learn isotropic and torsional representations of biomolecular structureStructural bio & protein designRank 39 Software exposes gene loss, pseudoknot layers and recombination graphs for inspectionTools & infrastructure