May 2026

Top 40

ML / AI methods

Recovering single-cell kinetics and trajectories from static and noisy measurements

Tools & infrastructure

Learned models link histology and spatial transcriptomics to predict expression and niches

Tools & infrastructure

New tools speed variant annotation, GWAS, and epigenomic and cytometry analysis

Systems biology

Correcting RNA degradation and hashtag demultiplexing in single-cell transcriptomics

ML / AI methods

Generative models map mass spectra directly to candidate molecular structures

6 Benchmarks for AI virtual cell models are being tested for scientific validityML / AI methods

7 Learned multimodal and graph representations for protein and RNA predictionML / AI methods

8 Learned predictors score protein interactions, variant effects, and peptide activityML / AI methods

9 Regional brain organization metrics test normative models, criticality, and morphometrySystems biology

10 Benchmarks and learned models expose gaps in metagenomic analysis softwareML / AI methods

11 Internal ground truths benchmark RNA-seq transcript and expression inference toolsGenomics

12 Integrating diverse variant and annotation data to improve genetic risk predictionGenomics

13 Sequence- and structure-based models predict protein function and dynamicsML / AI methods

14 Learned latents steer protein conformations and encode evolutionary structureML / AI methods

15 Graph and language-model encoders advance drug-target and synergy predictionStructural bio & protein design

16 Reproducible environments, DNA library design and standard formats for biology toolsStructural bio & protein design

17 Design-aware statistical models for differential analysis of omics and imaging dataSystems biology

18 Pretrained generative models extend to fMRI forecasting, diagnosis, and imagerySystems biology

19 Benchmarks and packaged pipelines standardize omics analysis toolsTools & infrastructure

20 Computational models link germinal center B cell states to antibody affinity maturationGenomics

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21 Mechanistic models link cell-scale rules to invasion, containment and therapy outcomesSystems biology

22 Multi-omic and structural data are converted into drug and target prioritization outputsGenomics

23 MD ensembles and replica-exchange sampling map folding and binding pathwaysStructural bio & protein design

24 LLM agents and multimodal models convert literature and spectra into molecular knowledgeTools & infrastructure

25 Graph neural networks model molecular interactions, drug synergy and disease driversSystems biology

26 Chromatin structure and nucleosome states inferred from sequencing and contact mapsStructural bio & protein design

27 Biophysical models link ion channel, noise and modulation to network firing dynamicsSystems biology

28 Models infer microbial and viral traits from large genomic and metagenomic datasetsGenomics

29 Comparative genomics partitions duplication, transfer and synteny across lineagesGenomics

30 MD and cofolding models probe conformational states in kinases, Aβ, and HIV-1 EnvStructural bio & protein design

31 Reproducible tools for assessing and streamlining omics data analysis workflowsTools & infrastructure

32 Models link non-genetic B cell state dynamics to antibody affinity maturationSystems biology

33 Chromosome-level assemblies link genome gigantism and gene loss to lineage evolutionGenomics

34 Computational models link genetic variants to RNA binding and cell-type expressionTools & infrastructure

35 Simulation methods extend to cyclic peptides, non-canonical residues and polypeptoidsStructural bio & protein design

36 MD simulations link conformational states to membrane binding and organizationStructural bio & protein design

37 Isoform-resolved single-cell and single-molecule methods quantify transcript variantsEpigenomics

38 Free energy and coarse-grained physics methods for biomolecular binding and interfacesStructural bio & protein design

39 Transformer and deep learning tools benchmarked against established genomics methodsGenomics

40 Refined inference of tumor methylation, structural variants and clonal structureSingle-cell