Week 33, 2026 · Aug 10 – Aug 16

Top 40

Systems biology

Bifurcation structure and heterogeneity determine persistence beyond threshold indices

Single-cell

Encoding spatial and relational structure in high-dimensional omics analysis

ML / AI methods

Learned multimodal and graph representations for protein and RNA prediction

Genomics

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

Systems biology

Regional brain organization metrics test normative models, criticality, and morphometry

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

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

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

9 Generative models steered by RL, fragments, and SMARTS for molecule and linker designStructural bio & protein design

10 Benchmark baselines and transfer conditions reshape reported gains in biological MLML / AI methods

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

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

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

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

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

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

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

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

19 Physical and quantum-derived references inform learned models of molecular propertiesML / AI methods

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

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

22 Cross-cohort tests expose limits of EEG, vocal, and transcriptomic biomarkersML / AI methods

23 Graph and transformer models infer regulatory networks and disease-linked RNAsML / AI methods

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

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

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

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

28 Benchmarks and packaged pipelines standardize omics analysis toolsTools & infrastructure

29 Network models nominate interventions from omics and screening dataSystems biology

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

31 Sequencing and inference methods resolve nucleic acid sequence, structure, and usageGenomics

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

33 Ensemble and free-energy methods now resolve RNA, protein and ligand binding physicsStructural bio & protein design

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

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

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