Ge F, Wang Y, Agerbo E, et al. Contrasting Risk Profiles for Suicide Attempt and Suicide Using Danish Registers and Genetic Data. JAMA psychiatry. 2025. doi:10.1001/jamapsychiatry.2025.3444
Publications
Ochoa-Urrea M, Butler EA, Bruenger T, et al. Insights Into -Related Epilepsy From 586 People: Variant Penetrance, Phenotypic Spectrum, and Treatment Outcomes. Neurology. 2025;105(9):e214235. doi:10.1212/WNL.0000000000214235
Chaudhary R, Moorhead G, Park R, et al. Long-term Survival and Molecular Biomarker Evaluation of a Phase II Cetuximab and Nivolumab Clinical Trial in Recurrent/Metastatic Head and Neck Cancer. Clinical cancer research : an official journal of the American Association for Cancer Research. 2025. doi:10.1158/1078-0432.CCR-25-2201
Barker KS, Zhang Q, Peters TL, et al. Relative contributions of the ERG11 and MRR1A mutations to fluconazole resistance in Clade III Candidozyma (Candida) auris clinical isolates. Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases. 2025. doi:10.1016/j.cmi.2025.10.009
Valencia C, Nathan A, Kang JB, Rumker L, Lee H, Raychaudhuri S. Modeling heterogeneity in single-cell perturbation states enhances detection of response eQTLs. Nature genetics. 2025. doi:10.1038/s41588-025-02344-6
St Laurent JD, Xu GD, Ying AW, et al. Shifted assembly and function of mSWI/SNF family subcomplexes underlie targetable dependencies in dedifferentiated endometrial carcinomas. Nature genetics. 2025. doi:10.1038/s41588-025-02333-9
Hemberg M, Marini F, Ghazanfar S, et al. Insights, opportunities, and challenges provided by large cell atlases. Genome biology. 2025;26(1):358. doi:10.1186/s13059-025-03771-8
Mansell RP, Müller S, Yang JS, et al. Ether lipids influence cancer cell fate by modulating iron uptake. bioRxiv : the preprint server for biology. 2025. doi:10.1101/2024.03.20.585922
PMCID
PMC10983928
Ludin A, Stirtz GL, Tal A, et al. CRATER tumor niches facilitate CD8 T cell engagement and correspond with immunotherapy success. Cell. 2025. doi:10.1016/j.cell.2025.09.021
Colin-Leitzinger C, Mekonnen YA, Narvaez-Bandera I, et al. A machine learning framework for classifying lipids in untargeted metabolomics using mass-to-charge ratios and retention times. Metabolomics : Official journal of the Metabolomic Society. 2025;21(6):151. doi:10.1007/s11306-025-02343-y