Week 22, 2026 · May 25 – May 31

Top 40

ML / AI methods

Benchmarking segmentation and synthetic ground truth for 3D tissue and organoid imaging

ML / AI methods

Generative models map mass spectra directly to candidate molecular structures

Systems biology

Design-aware statistical models for differential analysis of omics and imaging data

ML / AI methods

Explicit latent structure for single-cell perturbation response and multi-omic modeling

Genomics

Context-aware models refine variant calling, eQTL mapping and polygenic prediction

6 Bifurcation structure and heterogeneity determine persistence beyond threshold indicesSystems biology

7 Spatial and single-cell models infer multicellular motifs, regulators and disease linksSingle-cell

8 Constraints and cross-feeding shape inferred metabolic fluxes and microbial nichesSystems biology

9 LLM agents automate bioinformatics workflows with verifiable, grounded outputsML / AI methods

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

11 Protein language model embeddings enable sequence-based prediction of protein traitsML / AI methods

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

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

14 New tools for recombination, metagenomic decontamination, and microbial community designTools & infrastructure

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

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

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

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

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

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

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

22 Benchmarks and packaged pipelines standardize omics analysis toolsTools & infrastructure

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

24 New tools speed variant annotation, GWAS, and epigenomic and cytometry analysisTools & infrastructure

25 Simulations Link RNA Modifications to Conformation and Electronic StructureStructural bio & protein design

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

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

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

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

30 Transformer and deep learning tools benchmarked against established genomics methodsGenomics

31 Learned models link histology and spatial transcriptomics to predict expression and nichesTools & infrastructure

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

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

34 Comparative genomics partitions duplication, transfer and synteny across lineagesGenomics

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

36 Correcting RNA degradation and hashtag demultiplexing in single-cell transcriptomicsSystems biology

37 Reduced recurrent models reproduce complex dynamics across neural and molecular systemsSystems biology

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

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

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