DeepTetrad: high‐throughput image analysis of meiotic tetrads by deep learning inArabidopsis thaliana-Reference-Cited by-同舟云学术

DeepTetrad: high‐throughput image analysis of meiotic tetrads by deep learning inArabidopsis thaliana

Published:2019-10-22 Issue:2 Volume:101 Page:473-483
ISSN:0960-7412
Container-title:The Plant Journal
language:en
Short-container-title:Plant J

Author:

Lim Eun‐Cheon¹,Kim Jaeil¹,Park Jihye¹,Kim Eun‐Jung¹,Kim Juhyun¹,Park Yeong Mi¹,Cho Hyun Seob¹,Byun Dohwan¹,Henderson Ian R.²,Copenhaver Gregory P.³^ORCID,Hwang Ildoo¹,Choi Kyuha¹^ORCID

Affiliation:

1. Department of Life Sciences Pohang University of Science and Technology Pohang Gyeongbuk Republic of Korea

2. Department of Plant Sciences University of Cambridge Cambridge CB2 3EA UK

3. Department of Biology and the Integrative Program for Biological and Genome Sciences University of North Carolina at Chapel Hill Chapel Hill NC USA

Funder

Rural Development Administration

National Science Foundation

National Research Foundation of Korea

Publisher

Wiley

Subject

Cell Biology,Plant Science,Genetics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/tpj.14543

Reference48 articles.

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2. DeepCell 2.0: Automated cloud deployment of deep learning models for large‐scale cellular image analysis;Bannon D.;bioRxiv,2018

3. Fluorescent Arabidopsis tetrads: a visual assay for quickly developing large crossover and crossover interference data sets

4. The Role of AtMUS81 in Interference-Insensitive Crossovers in A. thaliana

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