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Csaba Molnár
Csaba Molnár
Postdoctoral Associate
Verified email at broadinstitute.org - Homepage
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Cited by
Cited by
Year
Data-analysis strategies for image-based cell profiling
JC Caicedo, S Cooper, F Heigwer, S Warchal, P Qiu, C Molnar, ...
Nature methods 14 (9), 849-863, 2017
4362017
Evaluation of deep learning strategies for nucleus segmentation in fluorescence images
JC Caicedo, J Roth, A Goodman, T Becker, KW Karhohs, M Broisin, ...
BioRxiv, 335216, 2019
2112019
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
962020
Green Silver and Gold Nanoparticles: Biological Synthesis Approaches and Potentials for Biomedical Applications
A Rónavári, N Igaz, DI Adamecz, B Szerencsés, C Molnar, Z Kónya, ...
Molecules 26 (4), 844, 2021
842021
Accurate morphology preserving segmentation of overlapping cells based on active contours
C Molnar, IH Jermyn, Z Kato, V Rahkama, P Östling, P Mikkonen, ...
Scientific Reports 6, 32412, 2016
742016
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
652017
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
612018
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
482018
Impact of the morphology and reactivity of nanoscale zero-valent iron (NZVI) on dechlorinating bacteria
A Rónavári, M Balázs, P Tolmacsov, C Molnár, I Kiss, Á Kukovecz, ...
Water research 95, 165-173, 2016
472016
Hsp70-associated chaperones have a critical role in buffering protein production costs
Z Farkas, D Kalapis, Z Bódi, B Szamecz, A Daraba, K Almási, K Kovács, ...
eLife 7, e29845, 2018
262018
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
142018
A multi-layer phase field model for extracting multiple near-circular objects
C Molnar, Z Kato, I Jermyn
Pattern Recognition (ICPR), 2012 21st International Conference on, 1427-1430, 2012
92012
Active contours for selective object segmentation
J Molnar, AI Szucs, C Molnar, P Horvath
2016 IEEE Winter Conference on Applications of Computer Vision (WACV), 1-9, 2016
72016
A New Model for the Segmentation of Multiple, Overlapping, Near-Circular Objects
C Molnar, Z Kato, IH Jermyn
Digital Image Computing: Techniques and Applications (DICTA), 2015 …, 2015
62015
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), 1-9, 2021
52021
An Object Splitting Model Using Higher-Order Active Contours for Single-Cell Segmentation
J Molnar, C Molnar, P Horvath
International Symposium on Visual Computing, 24-34, 2016
32016
Gene loss and compensatory evolution promotes the emergence of morphological novelties in budding yeast
Z Farkas, K Kovács, Z Sarkadi, D Kalapis, G Fekete, F Birtyik, F Ayaydin, ...
Nature Ecology & Evolution, 1-11, 2022
22022
Genome-wide RNAi screen identifies novel players in human 60S subunit biogenesis including key enzymes of polyamine metabolism
K Dörner, L Badertscher, B Horváth, R Hollandi, C Molnár, T Fuhrer, ...
Nucleic Acids Research, 2022
12022
Rapidly evaluating cancer dependencies by label-free imaging of zero-passage primary cells
M Al-Jazrawe, C Molnar, N Rindtorff, S Blum, W Colgan, M Alimova, ...
Cancer Research 82 (12_Supplement), 639-639, 2022
2022
Variational methods for shape modelling
C Molnár
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Articles 1–20