Top 40
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Rank 1
ML / AI methods
Machine learning models score and generate ligands for defined protein binding sites
Recent preprints and publications extend generative design and affinity prediction to fragments, binders, and multitarget uncertainty-aware scoring.
9 preprints · 3 published · ↑ 2.3× vs 4-wk avg
Rank 2 Structural bio & protein design
Simulations link structural plasticity and surface charge to nucleic acid binding
Residue-level MD and coarse-grained models now quantify how RNA-binding plasticity and charge govern nucleic acid interactions.
3 preprints · 2 published · ↑ 2.1× vs 4-wk avg
Rank 3 Structural bio & protein design
Relational deep learning for drug-target interaction and binding affinity prediction
Late-2025 reports combine graph attention, hybrid sequence architectures, and language-model embeddings for drug-target prediction.
1 preprint · 8 published · ↑ 2.0× vs 4-wk avg
Rank 4 ML / AI methods
Histology is coupled with omics, text, and graph models for spatial tissue analysis
Recent preprints and publications pair pretrained histology representations with genomic, text, and spatial omics inputs.
8 preprints · 4 published · ↑ 1.9× vs 4-wk avg
Rank 5 Systems biology
Multi-omics fusion models predict BRAF inhibitor sensitivity in GDSC cell lines
Recent preprints test fusion architectures and protein network embeddings for BRAF inhibitor response in GDSC cell lines.
3 preprints · 5 published · ↑ 1.8× vs 4-wk avg
Rank 6 Mechanistic models infer treatment response dynamics from sparse or indirect data↑ 1.7×Systems biologyRank 7 Computational methods resolve cell identity and spatial context in single-cell data↑ 1.6×Single-cellRank 8 Computational methods for disordered, multistate, and membrane-embedded protein systems↑ 1.6×Structural bio & protein designRank 9 Spatial indexing and geometric windows enable structure-level comparison of biomolecules↑ 1.8×Tools & infrastructureRank 10 Geometric models link cell shape and mechanics to multicellular developmental behavior↑ 1.6×ML / AI methodsRank 11 Latent representations of multiscale neural activity across recording modalities↑ 1.5×ML / AI methodsRank 12 Graph and literature-grounded AI generate and trace biomedical hypothesesML / AI methodsRank 13 Chromosome-scale assemblies link genome architecture to specialized metabolite evolutionGenomicsRank 14 Learned models encode biological structure in spatial and single-cell transcriptomicsML / AI methodsRank 15 Benchmarked callers resolve subclonal, rDNA, and allelic variation across sequencing dataGenomicsRank 16 Machine learning for RNA binders, drug sensitivity, protein function, and effectorsML / AI methodsRank 17 Multiscale models couple microbial competition, biofilm control and infection spreadSystems biologyRank 18 Extending GWAS to admixed populations, federated analysis, and non-additive effectsGenomicsRank 19 Splicing variation, cryptic exons and chromatin-RNA contacts shape gene regulationTranscriptomicsRank 20 Auditing and completing reference genomes to judge reliability before comparative useGenomics
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Rank 21 Models of E/I recurrent networks link criticality to spectra, avalanches and memorySystems biologyRank 22 Software tools for organizing, searching and benchmarking omics and imaging datasetsTools & infrastructureRank 23 Genome-scale sampling resolves marine microbial, algal, and coral lineage structureGenomicsRank 24 Genomic AMR prediction faces calibration, workflow and sampling-bias limitsGenomicsRank 25 Correcting platform-level measurement effects in methylation and genotype inferenceEpigenomicsRank 26 Transmission models quantify arbovirus spread, sparse-outbreak rates and spillover riskSystems biologyRank 27 New methods refine mutation attribution, metastasis reconstruction and chromatin tracingEpigenomicsRank 28 Learned sequence embeddings advance viral taxonomy and eDNA sequence annotationML / AI methodsRank 29 Imaging and barcoding readouts link gene perturbations to single-cell phenotypesSingle-cellRank 30 Single-cell and spatial profiling map tissue heterogeneity in development and diseaseSingle-cellRank 31 Noise propagation constrains causal gene inference from static expression dataSystems biologyRank 32 Biophysical models link axonal structure and stimulation physics to neural functionSystems biologyRank 33 Reliability of single-cell and gene network inference under noisy, incomplete dataSingle-cellRank 34 Learned models and acquisition design extend peptide and proteoform identificationProteomicsRank 35 Scoring protein mutations, PROTAC ternary complexes and NMR-consistent structuresStructural bio & protein designRank 36 Causal and non-additive models dissect plasma protein and disease genetic architectureGenomicsRank 37 Long-read profiling of retrotransposons and isoforms in aged brain and neuronsGenomicsRank 38 Learned models guide iterative virtual screening for SARS-CoV-2 and PLK2 inhibitorsStructural bio & protein design