Week 14, 2026 · Mar 30 – Apr 5

Top 40

ML / AI methods

Deep learning automates microscopy and histology image analysis with less labelled data

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

Structural bio & protein design

MD ensembles and replica-exchange sampling map folding and binding pathways

ML / AI methods

Benchmarks and learned models expose gaps in metagenomic analysis software

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

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

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

9 Structure-aware language models detect resistance genes and map variant activityML / AI methods

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

11 Recovering single-cell kinetics and trajectories from static and noisy measurementsML / AI methods

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

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

14 Ancient and phased human genomes test selection and imputation inference methodsGenomics

15 Transformer and deep learning tools benchmarked against established genomics methodsGenomics

16 Faster folding inference and deterministic MD clustering reshape conformational samplingML / AI methods

17 Graph storage and streaming parsers reshape population-scale variant computationTools & infrastructure

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

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

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

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

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

23 Comparative genomics partitions duplication, transfer and synteny across lineagesGenomics

24 Benchmarks and tools expose technical biases in sequencing-based genomic assaysEpigenomics

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

26 Encoding spatial and relational structure in high-dimensional omics analysisSingle-cell

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

28 Adhesion, noise, and discretization shape collective and single-cell migration modelsSystems biology

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

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

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

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

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

34 Noise, feedback and network structure shape emergent states in biological modelsSystems biology

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

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

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

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

39 Benchmarks probe AlphaFold model accuracy across peptides, RNA, and antibody complexesStructural bio & protein design

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