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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
6902019
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
1972021
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
1832021
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
1042022
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
982019
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
982019
MMSplice: modular modeling improves the predictions of genetic variant effects on splicing
J Cheng, TYD Nguyen, KJ Cygan, MH «elik, WG Fairbrother, J Gagneur
Genome biology 20 (1), 1-15, 2019
952019
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
762018
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
672017
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
622017
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
522018
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
302018
Kipoi: accelerating the community exchange and reuse of predictive models for genomics
Ž Avsec
ICML Workshop for Computational Biology, 2018
292018
Deep learning at base-resolution reveals motif syntax of the cis-regulatory code
Z Avsec, M Weilert, A Shrikumar, A Alexandari, S Krueger, K Dalal, ...
BioRxiv 737981, 2019
282019
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
212018
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
112019
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
92021
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
82018
CAGI 5 splicing challenge: improved exon skipping and intron retention predictions with MMSplice
J Cheng, MH «elik, TYD Nguyen, Ž Avsec, J Gagneur
Human mutation 40 (9), 1243-1251, 2019
72019
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Articles 1–20