Brunak, Søren

Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition

Rodriguez-Martin, B., Alvarez, E. G., Baez-Ortega, A., Zamora, J., Supek, F., Demeulemeester, J., Santamarina, M., Ju, Y. S., Temes, J., Garcia-Souto, D., et al. (2020) · Nature Genetics

Genomic variations and chromosomal abnormalitiesCancer Genomics and Diagnostics

Cited by 451

The sequences of 150,119 genomes in the UK Biobank

Halldorsson, B. V., Eggertsson, H. P., Moore, K. H. S., Hauswedell, H., Eiriksson, O., Ulfarsson, M. O., Palsson, G., Hardarson, M. T., Oddsson, A., Jensson, B. O., et al. (2022) · Nature

Genetic Associations and EpidemiologyGenomics and Rare Diseases

Cited by 448

Unexplored therapeutic opportunities in the human genome

Oprea, T. I., Bologa, C. G., Brunak, S., Campbell, A., Gan, G. N., Gaulton, A., Gomez, S. M., Guha, R., Hersey, A., Holmes, J., et al. (2018) · Nature Reviews Drug Discovery

Computational Drug Discovery MethodsBioinformatics and Genomic Networks

Cited by 378

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories

Placido, D., Yuan, B., Hjaltelin, J. X., Zheng, C., Haue, A. D., Chmura, P. J., Yuan, C., Kim, J., Umeton, R., Antell, G., et al. (2023) · Nature Medicine

Machine Learning in HealthcarePancreatic and Hepatic Oncology Research

Cited by 349

Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease

Folkersen, L., Fauman, E., Sabater-Lleal, M., Strawbridge, R. J., Frånberg, M., Sennblad, B., Baldassarre, D., Veglia, F., Humphries, S. E., Rauramaa, R., et al. (2017) · PLOS Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 343

Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records

Thorsen-Meyer, H.-C., Nielsen, A. B., Nielsen, A. P., Kaas-Hansen, B. S., Toft, P., Schierbeck, J., Strøm, T., Chmura, P. J., Heimann, M., Dybdahl, L., et al. (2020) · The Lancet Digital Health

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 336

Network biology concepts in complex disease comorbidities

Hu, J. X., Thomas, C. E., & Brunak, S. (2016) · Nature Reviews Genetics

Bioinformatics and Genomic NetworksMental Health Research Topics

Cited by 328

A large-scale analysis of tissue-specific pathology and gene expression of human disease genes and complexes

Lage, K., Hansen, N. T., Karlberg, E. O., Eklund, A. C., Roque, F. S., Donahoe, P. K., Szallasi, Z., Jensen, T. S., & Brunak, S. (2008) · Proceedings of the National Academy of Sciences

Bioinformatics and Genomic NetworksBiomedical Text Mining and Ontologies

Cited by 292

Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer

Akdemir, K. C., Le, V. T., Chandran, S., Li, Y., Verhaak, R. G., Beroukhim, R., Campbell, P. J., Chin, L., Dixon, J. R., Futreal, P. A., et al. (2020) · Nature Genetics

Genomics and Chromatin DynamicsChromatin Remodeling and Cancer

Cited by 283

A Nondegenerate Code of Deleterious Variants in Mendelian Loci Contributes to Complex Disease Risk

Blair, D. R., Lyttle, C. S., Mortensen, J. M., Bearden, C. F., Jensen, A. B., Khiabanian, H., Melamed, R., Rabadan, R., Bernstam, E. V., Brunak, S., et al. (2013) · Cell

Genetic Associations and EpidemiologyGenomics and Rare Diseases

Cited by 215

Co-evolution of transcriptional and post-translational cell-cycle regulation

Jensen, L. J., Jensen, T. S., de Lichtenberg, U., Brunak, S., & Bork, P. (2006) · Nature

Gene Regulatory Network AnalysisGenomics and Chromatin Dynamics

Cited by 184

Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review

Kenner, B., Chari, S. T., Kelsen, D., Klimstra, D. S., Pandol, S. J., Rosenthal, M., Rustgi, A. K., Taylor, J. A., Yala, A., Abul-Husn, N., et al. (2021) · Pancreas

AI in cancer detectionPancreatic and Hepatic Oncology Research

Cited by 158

Immune Profiling of Human Gut-Associated Lymphoid Tissue Identifies a Role for Isolated Lymphoid Follicles in Priming of Region-Specific Immunity

Fenton, T. M., Jørgensen, P. B., Niss, K., Rubin, S. J. S., Mörbe, U. M., Riis, L. B., Da Silva, C., Plumb, A., Vandamme, J., Jakobsen, H. L., et al. (2020) · Immunity

T-cell and B-cell ImmunologyIL-33, ST2, and ILC Pathways

Cited by 145

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models

Allesøe, R. L., Lundgaard, A. T., Hernández Medina, R., Aguayo-Orozco, A., Johansen, J., Nissen, J. N., Brorsson, C., Mazzoni, G., Niu, L., Biel, J. H., et al. (2023) · Nature Biotechnology

Bioinformatics and Genomic NetworksComputational Drug Discovery Methods

Cited by 111

Learning the natural history of human disease with generative transformers

Shmatko, A., Jung, A. W., Gaurav, K., Brunak, S., Mortensen, L. H., Birney, E., Fitzgerald, T., & Gerstung, M. (2025) · Nature

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 110

Two ancient human genomes reveal Polynesian ancestry among the indigenous Botocudos of Brazil

Malaspinas, A.-S., Lao, O., Schroeder, H., Rasmussen, M., Raghavan, M., Moltke, I., Campos, P. F., Sagredo, F. S., Rasmussen, S., Gonçalves, V. F., et al. (2014) · Current Biology

Forensic and Genetic ResearchGenetic diversity and population structure

Cited by 98

Predicting and elucidating the etiology of fatty liver disease: a machine learning modeling and validation study in the IMI DIRECT cohorts

Atabaki-Pasdar, N., Ohlsson, M., Viñuela, A., Frau, F., Pomares-Millan, H., Haid, M., Jones, A. G., Thomas, E. L., Koivula, R. W., Kurbasic, A., et al. (2020) · PLOS Medicine

Liver Disease Diagnosis and TreatmentAlcohol Consumption and Health Effects

Cited by 97

Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

The QT Interval International GWAS Consortium (QT-IGC), Lundby, A., Rossin, E. J., Steffensen, A. B., Acha, M. R., Newton-Cheh, C., Pfeufer, A., Lynch, S. N., Olesen, S.-P., Brunak, S., et al. (2014) · Nature Methods

Genetic Associations and EpidemiologyBioinformatics and Genomic Networks

Cited by 71

Chance of live birth: a nationwide, registry-based cohort study

Kolte, A. M., Westergaard, D., Lidegaard, Ø., Brunak, S., & Nielsen, H. S. (2021) · Human Reproduction

Reproductive Health and ContraceptionReproductive System and Pregnancy

Cited by 61

Association of variants near the bradykinin receptor B2 gene with angioedema in patients taking ACE inhibitors

Ghouse, J., Ahlberg, G., Andreasen, L., Banasik, K., Brunak, S., Schwinn, M., Larsen, I. H., Petersen, O., Sørensen, E., Ullum, H., et al. (2021) · Journal of the American College of Cardiology

Coagulation, Bradykinin, Polyphosphates, and AngioedemaGenetic Associations and Epidemiology

Cited by 24