| Deep learning: new computational modelling techniques for genomics G Eraslan, Ž Avsec, J Gagneur, FJ Theis Nature Reviews Genetics 20 (7), 389-403, 2019 | 851 | 2019 |
| Effective gene expression prediction from sequence by integrating long-range interactions Ž Avsec, V Agarwal, D Visentin, JR Ledsam, A Grabska-Barwinska, ... Nature methods 18 (10), 1196-1203, 2021 | 386 | 2021 |
| Base-resolution models of transcription-factor binding reveal soft motif syntax Ž Avsec, M Weilert, A Shrikumar, S Krueger, A Alexandari, K Dalal, ... Nature Genetics 53 (3), 354-366, 2021 | 308 | 2021 |
| Mapping single-cell data to reference atlases by transfer learning M Lotfollahi, M Naghipourfar, MD Luecken, M Khajavi, M Büttner, ... Nature biotechnology 40 (1), 121-130, 2022 | 210 | 2022 |
| MMSplice: modular modeling improves the predictions of genetic variant effects on splicing J Cheng, TYD Nguyen, KJ Cygan, MH Çelik, WG Fairbrother, Ž Avsec, ... Genome biology 20, 1-15, 2019 | 135 | 2019 |
| The Kipoi repository accelerates community exchange and reuse of predictive models for genomics Ž Avsec, R Kreuzhuber, J Israeli, N Xu, J Cheng, A Shrikumar, A Banerjee, ... Nature biotechnology 37 (6), 592-600, 2019 | 119 | 2019 |
| The Kipoi repository accelerates community exchange and reuse of predictive models for genomics Ž Avsec, R Kreuzhuber, J Israeli, N Xu, J Cheng, A Shrikumar, A Banerjee, ... Nature biotechnology 37 (6), 592-600, 2019 | 119 | 2019 |
| 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 | 116 | 2018 |
| Technical note on transcription factor motif discovery from importance scores (TF-MoDISco) version 0.5. 6.5 A Shrikumar, K Tian, Ž Avsec, A Shcherbina, A Banerjee, M Sharmin, ... arXiv preprint arXiv:1811.00416, 2018 | 84 | 2018 |
| Mutations in MDH2, encoding a Krebs cycle enzyme, cause early-onset severe encephalopathy S Ait-El-Mkadem, M Dayem-Quere, M Gusic, A Chaussenot, S Bannwarth, ... The American Journal of Human Genetics 100 (1), 151-159, 2017 | 78 | 2017 |
| Cis-regulatory elements explain most of the mRNA stability variation across genes in yeast J Cheng, KC Maier, Ž Avsec, P Rus, J Gagneur Rna 23 (11), 1648-1659, 2017 | 77 | 2017 |
| Query to reference single-cell integration with transfer learning M Lotfollahi, M Naghipourfar, MD Luecken, M Khajavi, M Büttner, Z Avsec, ... bioRxiv, 2020.07. 16.205997, 2020 | 41 | 2020 |
| Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks Ž Avsec, M Barekatain, J Cheng, J Gagneur Bioinformatics 34 (8), 1261-1269, 2018 | 34 | 2018 |
| Accurate proteome-wide missense variant effect prediction with AlphaMissense J Cheng, G Novati, J Pan, C Bycroft, A Žemgulytė, T Applebaum, A Pritzel, ... Science 381 (6664), eadg7492, 2023 | 32 | 2023 |
| Deep learning at base-resolution reveals motif syntax of the cis-regulatory code Ž Avsec, M Weilert, A Shrikumar, A Alexandari, S Krueger, K Dalal, ... BioRxiv 737981, 2019 | 31 | 2019 |
| Kipoi: accelerating the community exchange and reuse of predictive models for genomics Ž Avsec ICML Workshop for Computational Biology, 2018 | 28 | 2018 |
| Tf-Modisco v0. 4.4. 2-Alpha A Shrikumar, K Tian, A Shcherbina, Ž Avsec, A Banerjee, M Sharmin, ... arXiv preprint arXiv:1811.00416, 2018 | 23 | 2018 |
| Predicting mean ribosome load for 5’UTR of any length using deep learning A Karollus, Ž Avsec, J Gagneur PLoS computational biology 17 (5), e1008982, 2021 | 17 | 2021 |
| Assessing predictions of the impact of variants on splicing in CAGI5 SM Mount, Ž Avsec, L Carmel, R Casadio, MH Çelik, K Chen, J Cheng, ... Human mutation 40 (9), 1215-1224, 2019 | 14 | 2019 |
| Tf-modisco v0. 4.2. 2-alpha: Technical note A Shrikumar, K Tian, A Shcherbina, Ž Avsec, A Banerjee, M Sharmin, ... Preprint at arXiv https://arxiv. org/abs/1811.00416 v2, 2018 | 10 | 2018 |
Julien GagneurProfessor, TUM, MunichVerified email at in.tum.de
