Detalhe da pesquisa
1.
Multi-omics prediction of oat agronomic and seed nutritional traits across environments and in distantly related populations.
Theor Appl Genet
; 134(12): 4043-4054, 2021 Dec.
Artigo
em Inglês
| MEDLINE | ID: mdl-34643760
2.
Characterization of the transcriptional divergence between the subspecies of cultivated rice (Oryza sativa).
BMC Genomics
; 21(1): 394, 2020 Jun 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-32513103
3.
Leveraging genome-enabled growth models to study shoot growth responses to water deficit in rice.
J Exp Bot
; 71(18): 5669-5679, 2020 09 19.
Artigo
em Inglês
| MEDLINE | ID: mdl-32526013
4.
Allelic variants of OsHKT1;1 underlie the divergence between indica and japonica subspecies of rice (Oryza sativa) for root sodium content.
PLoS Genet
; 13(6): e1006823, 2017 Jun.
Artigo
em Inglês
| MEDLINE | ID: mdl-28582424
5.
Integrating Image-Based Phenomics and Association Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice.
Plant Physiol
; 168(4): 1476-89, 2015 Aug.
Artigo
em Inglês
| MEDLINE | ID: mdl-26111541
6.
Image Harvest: an open-source platform for high-throughput plant image processing and analysis.
J Exp Bot
; 67(11): 3587-99, 2016 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-27141917
7.
Introgression of novel traits from a wild wheat relative improves drought adaptation in wheat.
Plant Physiol
; 161(4): 1806-19, 2013 Apr.
Artigo
em Inglês
| MEDLINE | ID: mdl-23426195
8.
Genomic prediction of seed nutritional traits in biparental families of oat (Avena sativa).
Plant Genome
; 16(4): e20370, 2023 Dec.
Artigo
em Inglês
| MEDLINE | ID: mdl-37539632
9.
Statistical Methods for the Quantitative Genetic Analysis of High-Throughput Phenotyping Data.
Methods Mol Biol
; 2539: 269-296, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-35895210
10.
Gene Co-expression Network Analysis and Linking Modules to Phenotyping Response in Plants.
Methods Mol Biol
; 2539: 261-268, 2022.
Artigo
em Inglês
| MEDLINE | ID: mdl-35895209
11.
Generalizable approaches for genomic prediction of metabolites in plants.
Plant Genome
; 15(2): e20205, 2022 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-35470586
12.
Selection for seed size has uneven effects on specialized metabolite abundance in oat (Avena sativa L.).
G3 (Bethesda)
; 12(3)2022 03 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-34893823
13.
Translating insights from the seed metabolome into improved prediction for lipid-composition traits in oat (Avena sativa L.).
Genetics
; 217(3)2021 03 31.
Artigo
em Inglês
| MEDLINE | ID: mdl-33789350
14.
Improving Genomic Prediction for Seed Quality Traits in Oat (Avena sativa L.) Using Trait-Specific Relationship Matrices.
Front Genet
; 12: 643733, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-33868378
15.
Variance heterogeneity genome-wide mapping for cadmium in bread wheat reveals novel genomic loci and epistatic interactions.
Plant Genome
; 13(1): e20011, 2020 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-33016629
16.
Multi-trait random regression models increase genomic prediction accuracy for a temporal physiological trait derived from high-throughput phenotyping.
PLoS One
; 15(2): e0228118, 2020.
Artigo
em Inglês
| MEDLINE | ID: mdl-32012182
17.
Utilizing trait networks and structural equation models as tools to interpret multi-trait genome-wide association studies.
Plant Methods
; 15: 107, 2019.
Artigo
em Inglês
| MEDLINE | ID: mdl-31548847
18.
Predicting Longitudinal Traits Derived from High-Throughput Phenomics in Contrasting Environments Using Genomic Legendre Polynomials and B-Splines.
G3 (Bethesda)
; 9(10): 3369-3380, 2019 10 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-31427454
19.
Genomic Bayesian Confirmatory Factor Analysis and Bayesian Network To Characterize a Wide Spectrum of Rice Phenotypes.
G3 (Bethesda)
; 9(6): 1975-1986, 2019 06 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-30992319
20.
A Comprehensive Image-based Phenomic Analysis Reveals the Complex Genetic Architecture of Shoot Growth Dynamics in Rice (Oryza sativa).
Plant Genome
; 10(2)2017 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-28724075