| OUTRIDER: a statistical method for detecting aberrantly expressed genes in RNA sequencing data F Brechtmann, C Mertes, A Matusevičiūtė, VA Yépez, Ž Avsec, M Herzog, ... The American Journal of Human Genetics 103 (6), 907-917, 2018 | 180 | 2018 |
| Integration of variant annotations using deep set networks boosts rare variant association testing B Clarke, E Holtkamp, H Öztürk, M Mück, M Wahlberg, K Meyer, ... Nature Genetics 56 (10), 2271-2280, 2024 | 5 | 2024 |
| Evaluation of input data modality choices on functional gene embeddings F Brechtmann, T Bechtler, S Londhe, C Mertes, J Gagneur NAR Genomics and Bioinformatics 5 (4), lqad095, 2023 | 4 | 2023 |
| Functional gene embeddings improve rare variant polygenic risk scores S Londhe, J Lindner, Z Chen, E Holtkamp, FR Hölzlwimmer, FP Casale, ... bioRxiv, 2024.07. 22.604535, 2024 | | 2024 |
| Functional gene embeddings enable state-of-theart performance for a wide range of predictive tasks in genetics F Brechtmann, T Bechtler, S Londhe, C Mertes, B Clarke, O Stegle, ... EUROPEAN JOURNAL OF HUMAN GENETICS 32, 679-679, 2024 | | 2024 |
| OUTRIDER-OUTlier in RNA-Seq fInDER F Brechtmann, C Mertes, A Matuseviciute, V Yepez, J Gagneur | | 2020 |
| When the outlier is the signal: Denoising autoencoders to pinpoint causes of rare diseases from RNA-seq data C Mertes, I Scheller, F Brechtmann, A Matuseviciute, VA Yepez, ... EUROPEAN JOURNAL OF HUMAN GENETICS 27, 1711-1712, 2019 | | 2019 |
Christian MertesTechnical University of MunichVerified email at in.tum.de
