Follow
Patrick Trampert
Title
Cited by
Cited by
Year
Multi-omics enrichment analysis using the GeneTrail2 web service
D Stöckel, T Kehl, P Trampert, L Schneider, C Backes, N Ludwig, ...
Bioinformatics 32 (10), 1502-1508, 2016
1712016
Combining miRNA and mRNA expression profiles in Wilms tumor subtypes
N Ludwig, TV Werner, C Backes, P Trampert, M Gessler, A Keller, ...
International journal of molecular sciences 17 (4), 475, 2016
572016
Feature adaptive sampling for scanning electron microscopy
T Dahmen, M Engstler, C Pauly, P Trampert, N De Jonge, F Mücklich, ...
Scientific reports 6 (1), 25350, 2016
442016
Digital reality: a model-based approach to supervised learning from synthetic data
T Dahmen, P Trampert, F Boughorbel, J Sprenger, M Klusch, K Fischer, ...
AI Perspectives 1, 1-12, 2019
362019
Deep neural networks for analysis of microscopy images—synthetic data generation and adaptive sampling
P Trampert, D Rubinstein, F Boughorbel, C Schlinkmann, M Luschkova, ...
Crystals 11 (3), 258, 2021
332021
How should a fixed budget of dwell time be spent in scanning electron microscopy to optimize image quality?
P Trampert, F Bourghorbel, P Potocek, M Peemen, C Schlinkmann, ...
Ultramicroscopy 191, 11-17, 2018
322018
The Ettention software package
T Dahmen, L Marsalek, N Marniok, B Turoňová, S Bogachev, P Trampert, ...
Ultramicroscopy 161, 110-118, 2016
172016
Exemplar-based inpainting as a solution to the missing wedge problem in electron tomography
P Trampert, W Wang, D Chen, RBG Ravelli, T Dahmen, PJ Peters, ...
Ultramicroscopy 191, 1-10, 2018
162018
Linear chains of HER2 receptors found in the plasma membrane using liquid-phase electron microscopy
K Parker, P Trampert, V Tinnemann, D Peckys, T Dahmen, N de Jonge
Biophysical Journal 115 (3), 503-513, 2018
112018
Exemplar-based inpainting based on dictionary learning for sparse scanning electron microscopy
P Trampert, S Schlabach, T Dahmen, P Slusallek
Microscopy and Microanalysis 24 (S1), 700-701, 2018
102018
Sparse scanning electron microscopy data acquisition and deep neural networks for automated segmentation in connectomics
P Potocek, P Trampert, M Peemen, R Schoenmakers, T Dahmen
Microscopy and Microanalysis 26 (3), 403-412, 2020
82020
High-throughput large volume SEM workflow using sparse scanning and in-painting algorithms inspired by compressive sensing
F Boughorbel, P Potocek, M Hovorka, L Strakos, J Mitchels, T Vystavel, ...
Microscopy and Microanalysis 23 (S1), 150-151, 2017
82017
Spherically symmetric volume elements as basis functions for image reconstructions in computed laminography
P Trampert, J Vogelgesang, C Schorr, M Maisl, S Bogachev, N Marniok, ...
Journal of X-ray Science and Technology 25 (4), 533-546, 2017
62017
Marker detection in electron tomography: a comparative study
P Trampert, S Bogachev, N Marniok, T Dahmen, P Slusallek
Microscopy and Microanalysis 21 (6), 1591-1601, 2015
62015
Correlative fluorescence-and electron microscopy of whole breast cancer cells reveals different distribution of ErbB2 dependent on underlying actin
IN Dahmke, P Trampert, F Weinberg, Z Mostajeran, F Lautenschläger, ...
Frontiers in Cell and Developmental Biology 8, 521, 2020
52020
Dictionary-based Filling of the Missing Wedge in Electron Tomography
P Trampert, D Chen, S Bogachev, T Dahmen, P Slusallek
Microscopy and Microanalysis 22 (S3), 554-555, 2016
52016
Deep learning for sparse scanning electron microscopy
P Trampert, S Schlabach, T Dahmen, P Slusallek
Microscopy and Microanalysis 25 (S2), 158-159, 2019
42019
Sparse scanning electron microscopy for imaging and segmentation in connectomics
P Potocek, R Schoenmakers, P Trampert, T Dahmen, M Peemen
2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018
32018
Advanced recording schemes for electron tomography
T Dahmen, P Trampert, N de Jonge, P Slusallek
MRS Bulletin 41 (7), 537-541, 2016
32016
CausalTrail: Testing hypothesis using causal Bayesian networks
D Stöckel, F Schmidt, P Trampert, HP Lenhof
F1000Research 4, 2015
32015
The system can't perform the operation now. Try again later.
Articles 1–20