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Mojca Mattiazzi Usaj on Muck Rack

Mojca Mattiazzi Usaj

As seen in: Wiley Online Library, BioRxiv, Cell Systems, Cell Press
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Articles

From pixels to insights: Machine learning and deep learning for bioimage analysis

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By Mojca Mattiazzi Usaj, Mahta Jan, Allie Spangaro, Michelle Lenartowicz
| Wiley Online Library Verified
INTRODUCTION The demand for automated and quantitative acquisition and analysis of microscopy images has greatly increased, necessitating the development of powerful and efficient computational methods. In recent decades, artificial intelligence (AI), machine learning (ML), and deep learning (DL) have emerged as highly effective approaches with a multitude of applications in the biological sciences.
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PIFiA: Self-supervised Approach for Protein Functional Annotation from Single-Cell Imaging Data

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By Helena Friesen, Mojca Mattiazzi Usaj, Anastasia Razdaibiedina, Alexander V Brechalov
| BioRxiv
Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website.
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Single-cell image analysis to explore cell-to-cell heterogeneity in isogenic populations

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By Mojca Mattiazzi Usaj, Helena Friesen, Charles Boone, Brenda Andrews
| Cell Systems Verified
Summary Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship.
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