Suhre, Karsten

Machine Learning Approaches Reveal Metabolic Signatures of Incident Chronic Kidney Disease in Individuals With Prediabetes and Type 2 Diabetes

Huang, J., Huth, C., Covic, M., Troll, M., Adam, J., Zukunft, S., Prehn, C., Wang, L., Nano, J., Scheerer, M. F., et al. (2020) · Diabetes

Chronic Kidney Disease and DiabetesMetabolomics and Mass Spectrometry Studies

Cited by 60

Nanoparticle enrichment mass-spectrometry proteomics identifies protein-altering variants for precise pQTL mapping

Suhre, K., Venkataraman, G. R., Guturu, H., Halama, A., Stephan, N., Thareja, G., Sarwath, H., Motamedchaboki, K., Donovan, M. K. R., Siddiqui, A., et al. (2024) · Nature Communications

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 57

GFscore: a general nonlinear consensus scoring function for high-throughput docking.

Betzi, S., Suhre, K., Chétrit, B., Guerlesquin, F., & Morelli, X. (2006) · Journal of Chemical Information and Modeling

Computational Drug Discovery Methodsvaccines and immunoinformatics approaches

Cited by 51

Machine learning integration of multimodal data identifies key features of blood pressure regulation

Louca, P., Tran, T. Q. B., Toit, C. D., Christofidou, P., Spector, T. D., Mangino, M., Suhre, K., Padmanabhan, S., & Menni, C. (2022) · EBioMedicine

Blood Pressure and Hypertension StudiesSodium Intake and Health

Cited by 37

Mapping the Genetic Architecture of Gene Regulation in Whole Blood

Schramm, K., Marzi, C., Schurmann, C., Carstensen, M., Reinmaa, E., Biffar, R., Eckstein, G., Gieger, C., Grabe, H.-J., Homuth, G., et al. (2014) · PLoS ONE

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 33

PSEA: Phenotype Set Enrichment Analysis—A New Method for Analysis of Multiple Phenotypes

Ried, J. S., Döring, A., Oexle, K., Meisinger, C., Winkelmann, J., Klopp, N., Meitinger, T., Peters, A., Suhre, K., Wichmann, H. ‐., et al. (2012) · Genetic Epidemiology

Bioinformatics and Genomic NetworksGenetic Associations and Epidemiology

Cited by 21

Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Jo, T., Kim, J., Bice, P., Huynh, K., Wang, T., Arnold, M., Meikle, P. J., Giles, C., Kaddurah-Daouk, R., Saykin, A. J., et al. (2023) · eBioMedicine

Dementia and Cognitive Impairment ResearchMetabolomics and Mass Spectrometry Studies

Cited by 15

A genome-wide association study of mass spectrometry proteomics using a nanoparticle enrichment platform

Suhre, K., Chen, Q., Halama, A., Mendez, K., Dahlin, A., Stephan, N., Thareja, G., Sarwath, H., Guturu, H., Dwaraka, V. B., et al. (2025) · Nature Genetics

Genetic Associations and EpidemiologyAdvanced Proteomics Techniques and Applications

Cited by 14