Machine learning-aided quantification of antibody-based cancer immunotherapy by natural killer cells in microfluidic droplets-Reference-Cited by-同舟云学术

Machine learning-aided quantification of antibody-based cancer immunotherapy by natural killer cells in microfluidic droplets

Published:2020 Issue:13 Volume:20 Page:2317-2327
ISSN:1473-0197
Container-title:Lab on a Chip
language:en
Short-container-title:Lab Chip

Author:

Sarkar Saheli¹²³⁴^ORCID,Kang Wenjing¹²³⁴^ORCID,Jiang Songyao⁵⁶²³⁴,Li Kunpeng⁵⁶²³⁴,Ray Somak⁷⁸²³⁴,Luther Ed¹²³⁴,Ivanov Alexander R.⁷⁸²³⁴,Fu Yun⁵⁶²³⁴,Konry Tania¹²³⁴

Affiliation:

1. Department of Pharmaceutical Sciences

2. Northeastern University

3. Boston

4. USA

5. Department of Electrical and Computer Engineering

6. College of Engineering, and College of Computer and Information Science

7. Barnett Institute of Chemical and Biological Analysis

8. Department of Chemistry and Chemical Biology

Abstract

Comparative proteomic profiling and development of convolution neural network algorithm for quantifying discrete target interaction by engineered NK cells in microfluidic droplets.

Funder

National Institutes of Health

National Cancer Institute

National Science Foundation

National Institute of General Medical Sciences

Publisher

Royal Society of Chemistry (RSC)

Subject

Biomedical Engineering,General Chemistry,Biochemistry,Bioengineering

Link

http://pubs.rsc.org/en/content/articlepdf/2020/LC/D0LC00158A

Reference52 articles.