Week 13, 2026 · Mar 23 – Mar 29

Top 40

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ML / AI methods

Structure-aware statistical methods for single-cell and spatial transcriptomics inference

ML / AI methods

Brain-model alignment is probed via gradients, training dynamics, and EEG decoding

ML / AI methods

Locus-resolved tools scale variant interaction, colocalisation and SV detection

ML / AI methods

Encoding biological priors into graph, clock, and metabolic models

Systems biology

First-passage timing separable from steady-state output in stochastic regulatory models

6 Multi-agent LLM systems grounding biological queries in knowledge graphs and retrievalTools & infrastructure

7 Reliable Biomedical Prediction Models (auto label)ML / AI methods

8 Perturbation models and benchmarks reshaping therapeutic target nominationStructural bio & protein design

9 IsomiR-resolved modeling links isomiR targeting and extracellular vesicle provenanceSystems biology

10 Deep networks map genome-wide SNPs to quantitative phenotypes in grapevine and plantsGenomics

11 Structural variants in parasite genomes shape drug response and population structureGenomics

12 Scalable tools refine orthology and gene histories across diverse genome collectionsGenomics

13 ML-Guided Proteomics Methods Resolve Site-Level Structural and PTM ChangesMetabolomics

14 Protein language models encode nativeness, taxonomy, and memorization beyond trainingML / AI methods

15 Transformer and graph models learn regulatory links from DNA, RNA and protein sequencesML / AI methods

16 Inferring tissue and tumor states from spatial, single-cell, and metabolic dataMetabolomics

17 Benchmarks and diagnostics for inferring cell-level structure from single-cell…Tools & infrastructure

18 Protein Language Model Embeddings (auto label)ML / AI methods

19 Total RNA profiling joins coding and noncoding transcripts in single cellsTools & infrastructure

20 Biological Dynamics Modeling Frameworks (auto label)Structural bio & protein design

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21 Computational Nucleotide Sequence Design (auto label)Tools & infrastructure

22 Analytical choices shape accuracy in MS-based strain, variant and quantity inferenceProteomics

23 Computational metrics quantify resistance, foreign-genotype cells and CpG methylationEpigenomics

24 MD-informed models map allosteric couplings in receptors and AAA+ ATPasesStructural bio & protein design

25 Faster, portable tools for demultiplexing, QC, bin refinement and fungal ITS abundanceTools & infrastructure

26 Joint multiomic profiling links regulatory layers to gene expression within samplesGenomics

27 Interfaced workflow platforms make sequencing and spatial omics analyses reproducibleTools & infrastructure

28 In silico protein and peptide binder design with structure-based validationStructural bio & protein design

29 New computational methods for single-cell, spatial, and bulk transcriptomic analysisTools & infrastructure

30 Compact CpG selection and memory-limited active learning for predictive biochemistryEpigenomics

31 Personalized and reference-based models for high-dimensional biomedical dataSingle-cell

32 Cancer Genome Functional Landscapes (auto label)Genomics

33 Ensemble polymer models capture chromatin and disordered protein conformational statesEpigenomics

34 Phylogenetic inference under violated assumptions: diagnostics and correctionsSystems biology

35 Faster tools for protein dynamics: CEST fitting, flexibility, trajectory compressionTools & infrastructure

36 Coupling and modulation parameters shape oscillatory states across network modelsSystems biology

37 Docking workflows are coupling pose validation and MD setup into end-to-end pipelinesStructural bio & protein design

38 Molecular profiling defines disease-associated signatures in neurodegenerative conditionsProteomics

39 Recurrent CA3 dynamics may yield both place and time cell representationsSystems biology

40 Inferring temporal cell-state dynamics from snapshot single-cell and spatial dataSingle-cell

Week 13, 2026 · Mar 23 – Mar 29

Top 40

Structure-aware statistical methods for single-cell and spatial transcriptomics inference

Brain-model alignment is probed via gradients, training dynamics, and EEG decoding

Locus-resolved tools scale variant interaction, colocalisation and SV detection

Encoding biological priors into graph, clock, and metabolic models

First-passage timing separable from steady-state output in stochastic regulatory models

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