[WPS] 2025.03 W3

10/03/2025

1. Comparison of the multivariate genetic architecture of eight major psychiatric disorders across sex | Nature Genetics

2. Sequencing in over 50,000 cases identifies coding and structural variation underlying atrial fibrillation risk | Nature Genetics

3. The contribution of genetic determinants of blood gene expression and splicing to molecular phenotypes and health outcomes | Nature Genetics

4. Long-read RNA sequencing atlas of human microglia isoforms elucidates disease-associated genetic regulation of splicing | Nature Genetics

5. Plasma proteome variation and its genetic determinants in children and adolescents | Nature Genetics

6. ImmuneLENS characterizes systemic immune dysregulation in aging and cancer | Nature Genetics

7. Multiomic single-cell profiling identifies critical regulators of postnatal brain | Nature Genetics

8. Functional analysis of cancer-associated germline risk variants | Nature Genetics

9. Towards a more inductive world for drug repurposing approaches | Nature Machine Intelligence

10. A quantitative analysis of knowledge-learning preferences in large language models in molecular science | Nature Machine Intelligence

11. Contextual feature extraction hierarchies converge in large language models and the brain | Nature Machine Intelligence

12. Cell type–specific 3D-genome organization and transcription regulation in the brain | Science Advances

13. Leveraging prior knowledge to infer gene regulatory networks from single-cell RNA-sequencing data | Molecular Systems Biology

14. High order expression dependencies finely resolve cryptic states and subtypes in single cell data | Molecular Systems Biology

15. Single-molecule live-cell RNA imaging with CRISPR–Csm | Nature Biotechnology

16. Cell2fate infers RNA velocity modules to improve cell fate prediction | Nature Methods

17. Multiplexed spatial mapping of chromatin features, transcriptome and proteins in tissues | Nature Methods

18. Mapping the topography of spatial gene expression with interpretable deep learning | Nature Methods

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