Week 25, 2026 · Jun 15 – Jun 21

Top 40

Structural bio & protein design

Benchmarks probe AlphaFold model accuracy across peptides, RNA, and antibody complexes

Genomics

Sequencing and inference methods resolve nucleic acid sequence, structure, and usage

ML / AI methods

Protein language model embeddings enable sequence-based prediction of protein traits

Systems biology

Graph neural networks model molecular interactions, drug synergy and disease drivers

ML / AI methods

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

6 Comparative genomics partitions duplication, transfer and synteny across lineagesGenomics

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

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

9 Noise-driven dynamics shape neuronal firing, calcium states, and gait fluctuationsSystems biology

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

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

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

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

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

15 Benchmarks and packaged pipelines standardize omics analysis toolsTools & infrastructure

16 Generative models map mass spectra directly to candidate molecular structuresML / AI methods

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

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

19 Deep learning automates microscopy and histology image analysis with less labelled dataML / AI methods

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

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21 Shared embeddings fuse tissue images, spatial transcriptomes and molecular profilesML / AI methods

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

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

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

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

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

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

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

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

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

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

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

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

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

35 Transformer and deep learning tools benchmarked against established genomics methodsGenomics

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

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

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

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

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