Tamas Balassa
Tamas Balassa
Biological Research Centre, Szeged
Verified email at - Homepage
Cited by
Cited by
nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer
R Hollandi, A Szkalisity, T Toth, E Tasnadi, C Molnar, B Mathe, I Grexa, ...
Cell Systems, 2020
Intelligent image-based in situ single-cell isolation
C Brasko, K Smith, C Molnar, N Farago, L Hegedus, A Balind, T Balassa, ...
Nature communications 9 (1), 226, 2018
Phenotypic Image Analysis Software Tools for Exploring and Understanding Big Image Data from Cell-Based Assays
K Smith, F Piccinini, T Balassa, K Koos, T Danka, H Azizpour, P Horvath
Cell systems 6 (6), 636-653, 2018
Advanced cell classifier: user-friendly machine-learning-based software for discovering phenotypes in high-content imaging data
F Piccinini, T Balassa, A Szkalisity, C Molnar, L Paavolainen, K Kujala, ...
Cell systems 4 (6), 651-655. e5, 2017
A deep convolutional neural network approach for astrocyte detection
I Suleymanova, T Balassa, S Tripathi, C Molnar, M Saarma, Y Sidorova, ...
Scientific reports 8, 2018
A deep learning framework for nucleus segmentation using image style transfer
R Hollandi, A Szkalisity, T Toth, E Tasnadi, C Molnar, B Mathe, I Grexa, ...
Biorxiv, 580605, 2019
Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates
F Piccinini, T Balassa, A Carbonaro, A Diosdi, T Toth, N Moshkov, ...
Computational and structural biotechnology journal 18, 1287-1300, 2020
Hsp70-associated chaperones have a critical role in buffering protein production costs
Z Farkas, D Kalapis, Z Bodi, B Szamecz, A Daraba, K Almasi, K Kovacs, ...
Elife 7, e29845, 2018
Automatic deep learning-driven label-free image-guided patch clamp system
K Koos, G Oláh, T Balassa, N Mihut, M Rózsa, A Ozsvár, E Tasnadi, ...
Nature communications 12 (1), 1-11, 2021
Neuroinflammatory processes are augmented in mice overexpressing human heat-shock protein B1 following ethanol-induced brain injury
B Dukay, FR Walter, JP Vigh, B Barabási, P Hajdu, T Balassa, E Migh, ...
Journal of Neuroinflammation 18, 1-24, 2021
Environmental properties of cells improve machine learning-based phenotype recognition accuracy
T Toth, T Balassa, N Bara, F Kovacs, A Kriston, C Molnar, L Haracska, ...
Scientific reports 8 (1), 10085, 2018
Regression plane concept for analysing continuous cellular processes with machine learning
A Szkalisity, F Piccinini, A Beleon, T Balassa, IG Varga, E Migh, C Molnar, ...
Nature communications 12 (1), 2532, 2021
Probe set selection for targeted spatial transcriptomics
LB Kuemmerle, MD Luecken, AB Firsova, LB de Andrade e Sousa, ...
bioRxiv, 2022.08. 16.504115, 2022
Automatic deep learning driven label-free image guided patch clamp system for human and rodent in vitro slice physiology
K Koos, G Oláh, T Balassa, N Mihut, M Rózsa, A Ozsvár, E Tasnadi, ...
bioRxiv, 2020.05. 05.078162, 2020
Cell identification and phenotyping using classical machine learning and deep learning
T Balassa
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