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Žiga Avsec
Žiga Avsec
DeepMind
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Title
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Cited by
Year
Deep learning: new computational modelling techniques for genomics
G Eraslan, Ž Avsec, J Gagneur, FJ Theis
Nature Reviews Genetics 20 (7), 389-403, 2019
8512019
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
3862021
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
3082021
Mapping single-cell data to reference atlases by transfer learning
M Lotfollahi, M Naghipourfar, MD Luecken, M Khajavi, M BŁttner, ...
Nature biotechnology 40 (1), 121-130, 2022
2102022
MMSplice: modular modeling improves the predictions of genetic variant effects on splicing
J Cheng, TYD Nguyen, KJ Cygan, MH «elik, WG Fairbrother, Ž Avsec, ...
Genome biology 20, 1-15, 2019
1352019
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
1192019
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
1192019
OUTRIDER: a statistical method for detecting aberrantly expressed genes in RNA sequencing data
F Brechtmann, C Mertes, A Matusevičiūtė, VA Yťpez, Ž Avsec, M Herzog, ...
The American Journal of Human Genetics 103 (6), 907-917, 2018
1162018
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
842018
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
782017
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
772017
Query to reference single-cell integration with transfer learning
M Lotfollahi, M Naghipourfar, MD Luecken, M Khajavi, M BŁttner, Z Avsec, ...
bioRxiv, 2020.07. 16.205997, 2020
412020
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
342018
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
322023
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
312019
Kipoi: accelerating the community exchange and reuse of predictive models for genomics
Ž Avsec
ICML Workshop for Computational Biology, 2018
282018
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
232018
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
172021
Assessing predictions of the impact of variants on splicing in CAGI5
SM Mount, Ž Avsec, L Carmel, R Casadio, MH «elik, K Chen, J Cheng, ...
Human mutation 40 (9), 1215-1224, 2019
142019
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
102018
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