Author

S. Bolognin

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 2 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Organism:human· 3 Assay:organoid / primary culture· 3 Research Focus:cell type annotation· 2 Research Focus:drug response / drug discovery· 2 Approach:deep learning· 1

Frequent Co-Authors

J. C. Schwamborn· 3 shared C. Jordan· 2 shared M. Harasek· 2 shared P. Ertl· 2 shared S. Spitz· 2 shared A. S. Monzel· 1 shared A. Zagare· 1 shared B. Schaedl· 1 shared

Activity by Year

2019-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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3 shared papersBioengineering

J. C. Schwamborn

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3 papers

Recent·Most cited

Development of a multi-sensor integrated midbrain organoid-on-a-chip platform for studying Parkinson's disease

S. Spitz, S. Bolognin, K. Brandauer, J. Fuessl, P. Schuller, S. Schobesberger, C. Jordan, B. Schaedl, J. Grillari, H. D. Wanzenboeck, T. Mayr, M. Harasek, J. C. Schwamborn, P. Ertl

This study develops a multi-sensor organ-on-a-chip platform to monitor Parkinson's disease-related phenotypes in midbrain organoids and demonstrates its utility in drug screening.

bioRxiv · Aug 19, 2022 · PreprintBioengineering

Cultivation and characterization of human midbrain organoids in sensor integrated microfluidic chips

S. Spitz, C. Zanetti, S. Bolognin, M. N. Muwanigwa, L. M. Smits, E. Berger, C. Jordan, M. Harasek, J. C. Schwamborn, P. Ertl

This study develops a sensor-integrated microfluidic platform for long-term cultivation and non-invasive monitoring of human midbrain organoids, showing sustained viability and dopaminergic differentiation over 50 days.

bioRxiv · Dec 10, 2019 · PreprintBioengineering

Machine learning-assisted neurotoxicity prediction in human midbrain organoids

A. S. Monzel, K. Hemmer, T. Kaoma Mukendi, P. Lucarelli, I. Rosety, A. Zagare, S. Bolognin, P. Antony, S. L. Nickels, R. Krueger, F. Azuaje, J. C. Schwamborn

The paper develops a midbrain organoid system to model Parkinson's disease and introduces a machine learning pipeline for neurotoxicity prediction using high-content imaging data.

bioRxiv · Sep 19, 2019Pharmacology & Toxicology