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Michal Zielinski
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Highly accurate protein structure prediction with AlphaFold
J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ...
Nature 596 (7873), 583-589, 2021
219512021
Highly accurate protein structure prediction for the human proteome
K Tunyasuvunakool, J Adler, Z Wu, T Green, M Zielinski, A Žídek, ...
Nature 596 (7873), 590-596, 2021
20192021
Protein complex prediction with AlphaFold-Multimer
R Evans, M O’Neill, A Pritzel, N Antropova, A Senior, T Green, A Žídek, ...
biorxiv, 2021.10. 04.463034, 2021
16412021
A clinically applicable approach to continuous prediction of future acute kidney injury
N Tomašev, X Glorot, JW Rae, M Zielinski, H Askham, A Saraiva, ...
Nature 572 (7767), 116-119, 2019
8422019
Applying and improving AlphaFold at CASP14
J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ...
Proteins: Structure, Function, and Bioinformatics 89 (12), 1711-1721, 2021
2702021
Accurate proteome-wide missense variant effect prediction with AlphaMissense
J Cheng, G Novati, J Pan, C Bycroft, A Žemgulytė, T Applebaum, A Pritzel, ...
Science, eadg7492, 2023
2252023
Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records
N Tomašev, N Harris, S Baur, A Mottram, X Glorot, JW Rae, M Zielinski, ...
Nature Protocols 16 (6), 2765-2787, 2021
612021
Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs
D Rosenbaum, M Garnelo, M Zielinski, C Beattie, E Clancy, A Huber, ...
arXiv preprint arXiv:2106.14108, 2021
432021
Versioning for end-to-end machine learning pipelines
T van der Weide, D Papadopoulos, O Smirnov, M Zielinski, ...
Proceedings of the 1st Workshop on Data Management for End-to-End Machine …, 2017
322017
Developing Deep Learning Continuous Risk Models for Early Adverse Event Prediction in Electronic Health Records: an AKI Case Study
N Tomašev, X Glorot, JW Rae, M Zielinski, H Askham, A Saraiva, ...
22019
Versioned machine learning pipelines for batch experimentation
T Van der Weide, O Smirnov, M Zielinski, D Papadopoulos, ...
Machine Learning Systems workshop at NIPS, 2016
22016
Prediction of future adverse health events using neural networks by pre-processing input sequences to include presence features
N Tomasev, X Glorot, JW Rae, M Zielinski, A Mottram, H Askham, ...
US Patent 11,302,446, 2022
2022
A clinically applicable approach to continuous prediction of future acute kidney injury Open Website
N Tomasev, X Glorot, JW Rae, M Zielinski, H Askham, A Saraiva, ...
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