Single Cell Classification Using Statistical Learning on Mechanical Properties Measured by MEMS Tweezers-Reference-Cited by-同舟云学术

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Single Cell Classification Using Statistical Learning on Mechanical Properties Measured by MEMS Tweezers

Published:2022-01-09 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 35th International Conference on Micro Electro Mechanical Systems Conference (MEMS)
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Author:

Ahmadian Bahram¹,Mbujamba Deborah²,Gerbedoen Jean-Claude³,Kumemura Momoko⁴,Fujita Hiroyuki⁵,Collard Dominique³,Dabo-Niang Sophie⁶,Lagadec Chann⁷,Tarhan Mehmet C.¹

Affiliation:

1. Univ. Lille, CNRS, Centrale Lille, Polytechnique Hauts-de-France, Junia, UMR 8520-IEMN,Villeneuve d'Ascq,FRANCE

2. LIMMS/CNRS-IIS, UMI 2820, The University of Tokyo,Lille,FRANCE

3. CNRS, IIS, COL, Univ. Lille SMMiL-E Project,Lille,FRANCE

4. Kyushu Institute of Technology,Kita-Kyushu,JAPAN

5. Tokyo City University,Tokyo,JAPAN

6. Univ. Lille,CNRS, UMR 8524 - Laboratoire Paul Painlevé,Lille,FRANCE,59000

7. Univ. Lille,CNRS, Inserm, CHU Lille, Centre Oscar Lambret, UMR9020 - UMR-S 1277 - Canther - Cancer Heterogeneity, Plasticity and Resistance to Therapies,Lille,FRANCE,F-59000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9698823/9699435/09699466.pdf?arnumber=9699466

Reference8 articles.

1. Mechanical models for living cells—a review

2. A rapid and practical technique for real-time monitoring of biomolecular interactions using mechanical responses of macromolecules

3. Silicon Nanotweezers With Subnanometer Resolution for the Micromanipulation of Biomolecules

4. Invasive cancer cell lines exhibit biomechanical properties that are distinct from their noninvasive counterparts

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