A predictive model for seal condition in an automated patch clamp system
Author:
Funder
Research Grants Council, University Grants Committee
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Mechanical Engineering,General Materials Science
Link
https://link.springer.com/content/pdf/10.1007/s12213-023-00160-x.pdf
Reference34 articles.
1. Kodandaramaiah SB, Franzesi GT, Chow BY, Boyden ES, Forest CR (2012) Automated whole-cell patch-clamp electrophysiology of neurons in vivo. Nat Methods 9(6):585–587
2. Yajuan X, Xin L, Zhiyuan L (2012) A comparison of the performance and application differences between manual and automated patch-clamp techniques. Curr Chem Genomics 6:87
3. Neher E, Sakmann B (1992) The patch clamp technique. Sci Am 266(3):44–51
4. Koos K, Oláh G, Balassa T, Mihut N, Rózsa M, Ozsvár A, Tasnadi E, Barzó P, Faragó N, Puskás L (2021) Automatic deep learning-driven label-free image-guided patch clamp system. Nat Commun 12(1):1–11
5. Suchyna TM, Markin VS, Sachs F (2009) Biophysics and structure of the patch and the gigaseal. Biophys J 97(3):738–747
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