Large-scale tracking and classification for automatic analysis of cell migration and proliferation, and experimental optimization of high-throughput screens of neuroblastoma cells

Author:

Harder Nathalie12,Batra Richa2,Diessl Nicolle2,Gogolin Sina3,Eils Roland12,Westermann Frank3,König Rainer245,Rohr Karl12

Affiliation:

1. Department of Bioinformatics and Functional Genomics; Biomedical Computer Vision Group, BioQuant and Institute of Pharmacy and Molecular Biotechnology (IPMB), Heidelberg University; 69120 Heidelberg Germany

2. Division of Theoretical Bioinformatics; German Cancer Research Center (DKFZ); 69120 Heidelberg Germany

3. Division of Neuroblastoma Genomics; German Cancer Research Center (DKFZ); 69120 Heidelberg Germany

4. Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital; 07747 Jena Germany

5. Network Modeling, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute Jena; 07745 Jena Germany

Funder

BMBF project ENGINE (NGFN+)

BMBF MycNet

BMBF CSCC/IFB

BMBF FANCI (SysTec)

BMBF ImmunoQuant (e:Bio)

DAAD (Deutscher Akademischer Auslandsdienst, www.daad.de)

Publisher

Wiley

Subject

Cell Biology,Histology,Pathology and Forensic Medicine

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1. Machine Learning Approaches to 3D Models for Drug Screening;Biomedical Materials & Devices;2023-12-12

2. Multi-Object Dynamic Memory Network For Cell Tracking in Time-Lapse Microscopy Images;2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI);2021-04-13

3. Coupling cell detection and tracking by temporal feedback;Machine Vision and Applications;2020-04-18

4. Automated Blood Cell Detection and Counting via Deep Learning for Microfluidic Point-of-Care Medical Devices;IOP Conference Series: Materials Science and Engineering;2019-10-01

5. Cell dynamic morphology classification using deep convolutional neural networks;Cytometry Part A;2018-05-15

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