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 by Adam Hakim

Suggested by: Alon Vitenshtein


While Caenorhabditis elegans nematodes are powerful model organisms, quantification of visible phenotypes is still often labor-intensive, biased, and error-prone. We developed 'WorMachine', a three-step MATLAB-based image analysis software that allows automated identification of C. elegans worms, extraction of morphological features, and quantification of fluorescent signals. The program offers machine learning techniques which should aid in studying a large variety of research questions. The power of WorMachine assists in various assays such as: scoring binary and continuous sexual phenotypes, quantifying the effects of different RNAi treatments, and measuring intercellular protein aggregation. WorMachine is a 'quick and easy', high-throughput, automated, and unbiased analysis tool for measuring phenotypes.


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Adam Hakim
PhD student at Tel Aviv University
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Adam Hakim

PhD student at Tel Aviv University

Help us Improve WorMachine Oval 17

Hi all! let us know which morphological or fluorescent features you would like to see wormachine produce, and we will try to implement them in our next update. Be sure to check out the manual (inside "lib" folder in github link) for how to use the software, but feel free to contact us with questions.

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Posted: 3 years ago
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