Working with longitudinal data: quantifying developmental processes using function‐valued trait modeling-Reference-Cited by-同舟云学术

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Working with longitudinal data: quantifying developmental processes using function‐valued trait modeling

Published:2021-06 Issue:6 Volume:108 Page:905-908
ISSN:0002-9122
Container-title:American Journal of Botany
language:en
Short-container-title:Am. J. Bot.

Author:

Baker Robert L.¹^ORCID,Wang Diane R.²^ORCID

Affiliation:

1. Department of Biology Miami University Oxford OH45056USA

2. Agronomy Department Purdue University West Lafayette IN47907USA

Publisher

Wiley

Subject

Plant Science,Genetics,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ajb2.1677

Reference20 articles.

1. Bayesian estimation and use of high-throughput remote sensing indices for quantitative genetic analyses of leaf growth

2. Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape

3. Integrating transcriptomic network reconstruction and eQTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development

4. Mapping and Predicting Non-Linear Brassica rapa Growth Phenotypes Based on Bayesian and Frequentist Complex Trait Estimation

5. Utilizing random regression models for genomic prediction of a longitudinal trait derived from high‐throughput phenotyping

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Measuring leaf and root functional traits uncovers multidimensionality of plant responses to arbuscular mycorrhizal fungi;American Journal of Botany;2024-07

2. Dynamic growth QTL action in diverse light environments: characterization of light regime-specific and stable QTL in Arabidopsis;Journal of Experimental Botany;2023-06-12

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