Daniel Bojar
Daniel Bojar
University of Gothenburg - Wallenberg Centre for Molecular and Translational Medicine
Verified email at - Homepage
Cited by
Cited by
Designer exosomes produced by implanted cells intracerebrally deliver therapeutic cargo for Parkinson’s disease treatment
R Kojima, D Bojar, G Rizzi, GCE Hamri, MD El-Baba, P Saxena, ...
Nature communications 9 (1), 1305, 2018
Crystal structures of the phosphorylated BRI 1 kinase domain and implications for brassinosteroid signal initiation
D Bojar, J Martinez, J Santiago, V Rybin, R Bayliss, M Hothorn
The Plant Journal 78 (1), 31-43, 2014
Generalized extracellular molecule sensor platform for programming cellular behavior
L Scheller, T Strittmatter, D Fuchs, D Bojar, M Fussenegger
Nature Chemical Biology, 2018
A useful guide to lectin binding: machine-learning directed annotation of 57 unique lectin specificities
D Bojar, L Meche, G Meng, W Eng, DF Smith, RD Cummings, LK Mahal
ACS chemical biology 17 (11), 2993-3012, 2022
A CRISPR/Cas9-based central processing unit to program complex logic computation in human cells
H Kim, D Bojar, M Fussenegger
Proceedings of the National Academy of Sciences 116 (15), 7214-7219, 2019
Caffeine-inducible gene switches controlling experimental diabetes
D Bojar, L Scheller, G Charpin-El Hamri, M Xie, M Fussenegger
Nature Communications 9 (2318), 2018
Design and applications of a clamp for Green Fluorescent Protein with picomolar affinity
S Hansen, J Stüber, P Ernst, A Koch, D Bojar, A Batyuk, A Plückthun
Scientific Reports 7 (16292), 2017
Deep-learning resources for studying glycan-mediated host-microbe interactions
D Bojar, RK Powers, DM Camacho, JJ Collins
Cell Host & Microbe 29 (1), 132-144. e3, 2021
Using graph convolutional neural networks to learn a representation for glycans
R Burkholz, J Quackenbush, D Bojar
Cell Reports 35 (11), 109251, 2021
LectinOracle: A Generalizable Deep Learning Model for Lectin–Glycan Binding Prediction
J Lundstrøm, E Korhonen, F Lisacek, D Bojar
Advanced Science 9 (1), 2103807, 2022
Glycowork: A Python package for glycan data science and machine learning
L Thomès, R Burkholz, D Bojar
Glycobiology, 2021
Design of synthetic promoters for gene circuits in mammalian cells
P Saxena, D Bojar, M Fussenegger
Mammalian synthetic promoters, 263-273, 2017
The role of fucose-containing glycan motifs across taxonomic kingdoms
L Thomès, D Bojar
Frontiers in Molecular Biosciences 8, 755577, 2021
The Role of Protein Engineering in Biomedical Applications of Mammalian Synthetic Biology
D Bojar, M Fussenegger
Small, 2019
Generation of glucose-sensitive insulin-secreting beta-like cells from human embryonic stem cells by incorporating a synthetic lineage-control network
P Saxena, D Bojar, H Zulewski, M Fussenegger
Journal of Biotechnology, 2017
Glycoinformatics in the artificial intelligence era
D Bojar, F Lisacek
Chemical Reviews 122 (20), 15971-15988, 2022
Using Natural Language Processing to Learn the Grammar of Glycans
D Bojar, D Camacho, J Collins
bioRxiv, 2020
The best of both worlds: reaping the benefits from mammalian and bacterial therapeutic circuits.
D Bojar, M Fussenegger
Current Opinion in Chemical Biology 34, 11-19, 2016
Purity by design: Reducing impurities in bioproduction by stimulus-controlled global translational downregulation of non-product proteins
D Bojar, T Fuhrer, M Fussenegger
Metabolic Engineering, 2018
SweetOrigins: Extracting Evolutionary Information from Glycans
D Bojar, RK Powers, DM Camacho, JJ Collins
bioRxiv, 2020
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