Single-Cell Technologies
@SCTHungary
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Our mission is to bring state-of-the-art machine learning and visualization techniques into the world of biology research.
Joined May 2022
We at Single-Cell Technologies would like to wish a very successful New Year to all our current and future partners. Thank you for being part of our journey!
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What an amazing two days we had at our first ever multi-day Single-cell Isolation Workshop last week! A huge thank you to everyone who joined us, helped out, and made this such a success and we’re already looking forward to organizing the next one! https://t.co/MRuqyN33Q6
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Meet us there tomorrow! • Találkozzunk holnaptól a Millenárison!
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Science Expo 2025 We are excited to announce that Single-Cell Technologies (SCT) will be present at the 2025 Science Expo organized by the Hungarian Innovation Agency and HUN-REN, taking place at Millenáris, Budapest, from October 28–30. https://t.co/DP7Ervwmtn
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Science Expo 2025 We are excited to announce that Single-Cell Technologies (SCT) will be present at the 2025 Science Expo organized by the Hungarian Innovation Agency and HUN-REN, taking place at Millenáris, Budapest, from October 28–30. https://t.co/DP7Ervwmtn
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Last chance! Only 1 spot left and 1 day to go to register for our first-ever Single-Cell Isolation Workshop in Szeged (Nov 10–11, 2025). Learn sample prep, screening, image analysis & cell isolation! Register free: https://t.co/OtbiYB7YzH
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Celebrating the Markusovszky Lajos Prize We are proud to share that this summer, our collaborative research was honored with the Markusovszky Lajos Prize, awarded by Orvosi Hetilap (Hungarian Medical Journal). https://t.co/QJ3tXg5hCP
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We are excited to announce SCT's first ever multi-day Single-cell Isolation Workshop to be held at the Single Cell Centre, Szeged, Hungary on the November 10-11, 2025. Registration is free but places are limited https://t.co/OtbiYB7YzH
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European Symposium on Single Cell Proteomics Last week, we had the privilege to join the 6th European Symposium on Single Cell Proteomics (ESCP) in Vienna. September 1, 2025 https://t.co/Qz0dqluH5s
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The first article of 2024 where our software was used. "The Biology Image Analysis Software was used to evaluate HE images..." https://t.co/rXu12t3X3f
link.springer.com
GeroScience - The prevalence of chronic kidney disease (CKD) is increasing globally, especially in elderly patients. Uremic cardiomyopathy is a common cardiovascular complication of CKD,...
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Revolutionize your research with a fully automated pipeline for 3D cell cultures! BIAS offers deep learning based 3D nucleus segmentation combined with feature extraction and classification. The user-friendly and interactive display aids in visualizing your results.
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A freshly published Nature article ( https://t.co/l5tujGwaWo) emphasizes the crucial role of deep learning algorithms in analyzing microscopy images. We are thrilled that one of our most recent achievements, a fully segmented 3D human carcinoma was used to illustrate the method.
nature.com
Nature - Deep learning is driving the rapid evolution of algorithms that can automatically find and trace cells in a wide range of microscopy experiments.
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BIAS is an outstanding tool for the analysis of high-content screening data while providing rapid, fully automated, and unbiased assessment of biological samples. This example is from one of our publications ( https://t.co/HBdv9C7Twr) where we did a serology test for SARS-CoV-2.
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SCT announces biomedical and regulatory services in high-content screening, digital pathology and 3D imaging. https://t.co/P8mtE7kjeg For more information contact us at consulting@sct.bio.
linkedin.com
SCT announces biomedical and regulatory services in high-content screening, digital pathology and 3D imaging. For more information contact us at [email protected] or visit our website: https://lnk...
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We went on a joined retreat with the @BIOMAGlab from the @BiologicalRese1. We shared and shaped future plans, did some team building and had some fun. And the food was also exquisite. :)
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Using BIAS, we have developed an automated method to segment and cluster spheroid samples, enabling the identification of novel phenotypes. Our interactive clustering module effectively classified multicellular tumor spheroids into 3 distinct classes.
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First sneak peek of new functions in the upcoming BIAS 1.3 release. Revamped GUI and interactive deep-learning based phenotype classification. More updates will come soon, stay tuned :)
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Are you tired of using the same old techniques to study tumor spheroids? Using cutting-edge algorithms and AI to automate segmentation and analysis of complex 3D tumor spheroids, BIAS will identify and isolate each individual nucleus for you, saving you hours of laborious work!
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