Work

Toward a Fully Automated High-Throughput Phototransfection System

Year: 2010

Type: article

Abstract: We have designed and implemented a framework for creating a fully automated high-throughput phototransfection system. Integrated image processing, laser target position calculation, and stage movements show a throughput increase of > 23X over the current manual phototransfection method while the potential for even greater throughput improvements (> 110X) is described. A software tool for automated off-line single cell morphological measurements, as well as real-time image segmentation analysis, has also been constructed and shown to be able quantify changes in the cell before and after the process, successfully characterizing them, using metrics such as cell perimeter, area, major and minor axis length, and eccentricity values.

Source: JALA Journal of the Association for Laboratory Automation

DOI: 10.1016/j.jala.2010.03.003

Authors: David J. Cappelleri, Adam Halasz, Jai-Yoon Sul, Tae Kyung Kim, James Eberwine, Vijay Kumar

Institutions: Stevens Institute of Technology, West Virginia University, University of Pennsylvania

Language: English

Topic: Cell Image Analysis Techniques

Subfield: Biophysics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funder: National Institutes of Health

Award: Cellular logic of phenotype