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 | 212 | 2020 |
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 | 92 | 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 | 90 | 2017 |
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 | 87 | 2018 |
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 | 63 | 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 | 47 | 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 | 43 | 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 | 40 | 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 | 38 | 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 | 29 | 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 | 20 | 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 | 13 | 2021 |
Probe set selection for targeted spatial transcriptomics LB Kuemmerle, MD Luecken, AB Firsova, L Barros de Andrade e Sousa, ... Nature methods, 1-11, 2024 | 10 | 2024 |
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 | 4 | 2020 |
A topographic lung cell atlas reveals regional variation in cell-type specific gene programs and identifies healthy and diseased cellular neighborhoods C Samakovlis, A Firsova, SM Salas, L Kümmerle, X Abalo, L Larsson, ... | | 2024 |
Topographic atlas of cell states identifies regional gene expression in the adult human lung A Firsova, S Marco Salas, L Kuemmerle, X Abalo, L Larsson, ... | | 2024 |
Cell identification and phenotyping using classical machine learning and deep learning T Balassa | | 2021 |