Lugenbühl JF, Snijders C, Pernia CD, Estruch MS, Kenis G, Daskalakis NP. Corticosteroid-regulated gene transcription in SH-SY5Y-derived neurons: Insights into the mineralocorticoid and glucocorticoid receptor-mediated response. Journal of neuroendocrinology. 2025:e70021. doi:10.1111/jne.70021
Publications
Tercan B, Apolonio VH, Chagas VS, et al. Protocol for assessing distances in pathway space for classifier feature sets from machine learning methods. STAR protocols. 2025;6(2):103681. doi:10.1016/j.xpro.2025.103681
Haring B, Aragaki AK, Shimbo D, et al. Clonal Hematopoiesis of Indeterminate Potential and Incident Hypertension: Results From the Women’s Health Initiative. Hypertension (Dallas, Tex. : 1979). 2025;82(4):e70-e72. doi:10.1161/HYPERTENSIONAHA.124.24482
Lee MA, Brown JS, Farquhar CE, Loas A, Pentelute BL. Affinity selection-mass spectrometry with linearizable macrocyclic peptide libraries. Science advances. 2025;11(12):eadr1018. doi:10.1126/sciadv.adr1018
Wiggers CRM, Yüzügüldü B, Tadros NG, et al. Genome-wide CRISPR screen identifies IRF1 and TFAP4 as transcriptional regulators of Galectin-9 in T cell acute lymphoblastic leukemia. Science advances. 2025;11(12):eads8351. doi:10.1126/sciadv.ads8351
Nadig A, Thoutam A, Hughes M, et al. Consequences of training data composition for deep learning models in single-cell biology. bioRxiv : the preprint server for biology. 2025. doi:10.1101/2025.02.19.639127
Romanov A, Knappe GA, Ronsard L, et al. DNA origami vaccines program antigen-focused germinal centers. bioRxiv : the preprint server for biology. 2025. doi:10.1101/2025.02.21.639354
Lamichhane S, Dickens AM, Buchacher T, et al. Trajectories of microbiome-derived bile acids in early life - insights into the progression to islet autoimmunity. medRxiv : the preprint server for health sciences. 2025. doi:10.1101/2025.02.18.25322275
Chami N, Wang Z, Svenstrup V, et al. Genetic subtyping of obesity reveals biological insights into the uncoupling of adiposity from its cardiometabolic comorbidities. medRxiv : the preprint server for health sciences. 2025. doi:10.1101/2025.02.25.25322830
Nadig A, Thoutam A, Hughes M, et al. Consequences of training data composition for deep learning models in single-cell biology. bioRxiv : the preprint server for biology. 2025. doi:10.1101/2025.02.19.639127