Regression plane concept for analysing continuous cellular processes with machine learning

Regression plane concept for analysing continuous cellular processes with machine learning

High-content screening prompted the development of software enabling discrete phenotypic analysis of single cells. Here, the authors show that supervised continuous machine learning can drive novel discoveries in diverse imaging experiments and present the Regression Plane module of Advanced Cell Cl...

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Detalles Bibliográficos
Autores principales: Abel Szkalisity, Filippo Piccinini, Attila Beleon, Tamas Balassa, Istvan Gergely Varga, Ede Migh, Csaba Molnar, Lassi Paavolainen, Sanna Timonen, Indranil Banerjee, Elina Ikonen, Yohei Yamauchi, Istvan Ando, Jaakko Peltonen, Vilja Pietiäinen, Viktor Honti, Peter Horvath
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Science
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Acceso en línea:https://doaj.org/article/f49f0d2d8b5f4b588375e657d0654bfa
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Sumario:High-content screening prompted the development of software enabling discrete phenotypic analysis of single cells. Here, the authors show that supervised continuous machine learning can drive novel discoveries in diverse imaging experiments and present the Regression Plane module of Advanced Cell Classifier.

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