A deep-learning-based workflow to deal with the defocusing problem in high-throughput experiments-Reference-Cited by-同舟云学术

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A deep-learning-based workflow to deal with the defocusing problem in high-throughput experiments

Published:2022-05 Issue: Volume:11 Page:218-229
ISSN:2452-199X
Container-title:Bioactive Materials
language:en
Short-container-title:Bioactive Materials

Author:

Xue Yunfan,Qian Honglin,Li Xu,Wang Jing,Ren Kefeng,Ji Jian^ORCID

Funder

Fundamental Research Funds for the Central Universities

Zhejiang Provincial Ten Thousand Plan for Young Top Talents

National Natural Science Foundation of China

National Key Research and Development Program of China

National Key Research and Development Program of China Stem Cell and Translational Research

Higher Education Discipline Innovation Project

Publisher

Elsevier BV

Subject

Biomedical Engineering,Biomaterials,Biotechnology

Reference47 articles.

1. Combinatorial development of biomaterials for clonal growth of human pluripotent stem cells;Mei;Nat. Mater.,2010

2. Artificial niche microarrays for probing single stem cell fate in high throughput;Gobaa;Nat. Methods,2011

3. Substrate stiffness and matrix composition coordinately control the differentiation of liver progenitor cells;Kourouklis;Biomaterials,2016

4. Effect of size and crystalline phase of TiO2 nanotubes on cell behaviors: a high throughput study using gradient TiO2 nanotubes;Li;Bioactive Materials,2020

5. Immune-instructive polymers control macrophage phenotype and modulate the foreign body response in vivo;Rostam;Matter,2020

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