Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning is a research paper published in Archives of Toxicology (2021). On theSindex it has a DataRank of 0.542. It has been cited 36 times.
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Base Score Contribution
0.542
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →Engineering and Physical Sciences Research Council
Grant: EP/N013506/1
Engineering Blood Diagnostics: Integrated Platforms for Advanced Detection and Analysis
Biotechnology and Biological Sciences Research Council
Grant: BB/P026818/1
Open access deep learning solutions for imaging flow cytometry
National Institutes of Health
Grant: R35 GM122547
Life Science Research Network Wales
Grant: LSBF/R3-007
Medical Research Council
Grant: MR/R005699/1
National Institutes of Health
Grant: 3R35GM122547-02S1
Extracting rich information from biological images
FWCI
1.65
Citation Percentile
0.8%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Application of image-recognition techniques to automated micronucleus detection in the in vitro micronucleus assay
Additional file 1 of Application of image-recognition techniques to automated micronucleus detection in the in vitro micronucleus assay