Author

Stefan Konigorski

Hasso Plattner InstituteORCID 0000-0002-9966-6819Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetics· 2 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:GWAS / association mapping· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Christoph LippertiD· 2 shared Matthias KirchleriD· 2 shared Alva Rani JamesiD· 1 shared Charles N. J. RavaraniiD· 1 shared Christian Meltendorf· 1 shared Claudia SchurmanniD· 1 shared Erwin P. BöttingeriD· 1 shared Hannes A. BaukmanniD· 1 shared

Activity by Year

2021-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 18 mutual co-author links

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2 shared papersGenetics

Christoph LippertORCID

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3 papers

Recent·Most cited

GeneticsNature CommunicationsPeer-reviewedSep 10, 2022

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

Remo Monti, Pia Rautenstrauch, Mahsa Ghanbari…·Christoph Lippert

The paper performs a rare variant association study of 30 blood biomarkers in 191,971 UK Biobank individuals, identifying 193 gene-biomarker associations using functionally informed kernel-based tests.

15 citations

humanwhole-exome sequencing

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GeneticsBioinformaticsPeer-reviewedMay 31, 2022

transferGWAS: GWAS of images using deep transfer learning

Matthias Kirchler, Stefan Konigorski, Matthias Norden…·Christoph Lippert

transferGWAS applies deep transfer learning to medical images for GWAS, identifying 60 genomic regions associated with retinal fundus images, including 7 novel eye-related loci.

43 citationstop 3%

humanimaging

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Genetic & Genomic MedicineFrontiers in GeneticsPeer-reviewedOct 20, 2021

Interaction-based feature selection algorithm outperforms polygenic risk score in predicting Parkinson's Disease status

Jörn Klinger, Charles N. J. Ravarani, Hannes A. Baukmann…·Marco Florian Schmidt

The paper presents an interaction-based feature selection algorithm that outperforms polygenic risk scores in predicting Parkinson's Disease status using the PPMI dataset.

10 citations

humanwhole-genome sequencing

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