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Grid Screener: A Tool for Automated High-throughput Screening on Biochemical and Biological Analysis Platforms

Schilling, Marcel P. ORCID iD icon; Schmelzer, Svenja; Gómez, Joaquín Eduardo Urrutia; Popova, Anna A.; Levkin, Pavel A. ORCID iD icon; Reischl, Markus


Grid structures are common in high-throughput assays to parallelize experiments in biochemical or biological experiments. Manual analysis of grid images is laborious, time-consuming, expensive, and critical in terms of reproducibility. However, it is still common to do such analysis manually, as there is no standardized software for automated analysis. In this paper, we introduce a generic method to automatically detect grid structures in images and to perform flexible spot-wise analysis after successful grid detection. The deep learning-based approach of the grid structure detection allows being flexible concerning different grid types. The combination with a robust parameter estimation algorithm lowers the requirements of the detection quality and thus enhances robustness. Further, the method conducts semi-automated grid detection if a fully automated processing fails. An open-source software tool Grid Screener that implements the proposed methods is provided as a ready-for-use tool for researchers. The usability is demonstrated by taking different criteria into account, which are important for a successful application. We present the benefits of our proposed tool Grid Screener utilizing three different grid types in the context of high-throughput screening to show our contribution towards further lab automation. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000141260
Veröffentlicht am 16.12.2021
DOI: 10.1109/ACCESS.2021.3135709
Zitationen: 1
Web of Science
Zitationen: 2
Zitationen: 2
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Institut für Biologische und Chemische Systeme (IBCS)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 24.12.2021
Sprache Englisch
Identifikator ISSN: 2169-3536
KITopen-ID: 1000141260
HGF-Programm 47.14.02 (POF IV, LK 01) Information Storage and Processing in the Cell Nucleus
Erschienen in IEEE access
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Band 9
Seiten 166027-166038
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Vorab online veröffentlicht am 14.12.2021
Nachgewiesen in Dimensions
Web of Science
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