Positional cloning of <i>qNN1</i> on chromosome 16. by Xinxin Li (281237)

Shoot-to-root translocation of GmNN1/FT2a regulates soybean nodulation. by Xinxin Li (281237)

<i>GmNN1/FT2a</i> expression analysis. by Xinxin Li (281237)

Global Land Use Change Impacts on Soil Nitrogen Availability and Environmental Losses by Jing Wang (6206297)

Subjects:

Functions of <i>GmNN1/FT2a</i> in nitrogen nutrition and nodulation. by Xinxin Li (281237)

The GmNN1/FT2a-GmNFYA-C-GmENOD40 module regulates soybean nodulation. by Xinxin Li (281237)

Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 12 covariates chosen using subjective feature selection. by Dennis Ochola (11626912)

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Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 17 covariates selected after recursive feature selection. by Dennis Ochola (11626912)

Subjects:

Plant growth, nodulation, and N content as affected by manipulating of GmNN1/FT2a. by Xinxin Li (281237)

Expression of <i>GmNN1/FT2a</i> in various tissues of soybean plants. by Xinxin Li (281237)

GmNN1/FT2a interacted with GmNYFA-C in the BiFC assay. by Xinxin Li (281237)

Gene specific primers used for <i>GmNN1/FT2a</i> fine mapping. by Xinxin Li (281237)

Temporal profiles of the key BO-NN features. by Julia Berezutskaya (9080269)

“…Right plot show the gradual decrease in the TM tuning for the features highlighted in <b>c</b> as well as the gradual increase in the temporal response profile (i.e. optimal shifts for the prediction of the key BO-NN features using Praat features shown in <b>a</b>). …”

Phenotype and molecular identification of <i>GmNN1/FT2a</i> in stable transgenic soybean plants. by Xinxin Li (281237)

A proposed working model of how the GmNN1/FT2a-GmNYFA-C-GmENOD40 module regulates nodulation in soybean. by Xinxin Li (281237)

The G215S mutation decreases packaging of N and growth in primary differentiated human bronchial cells. by Hannah C. Kubinski (21213168)

Application of Machine Learning-Based Models to Understand and Predict Critical Flux of Oil-in-Water Emulsion in Crossflow Microfiltration by Henry J. Tanudjaja (12106715)

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Top k-NN clusters of metabolites decreased at 4 hours. by Zarazuela Zolkipli-Cunningham (5234186)

Top k-NN cluster of metabolites decreased at 30 minutes. by Zarazuela Zolkipli-Cunningham (5234186)

Inhibition and assessment of the biophysical gating properties of GluA2 and GluA2/A3 AMPA receptors using curcumin derivatives by Mohammad Qneibi (7314050)

“…Thus, the current study investigated novel curcumin derivatives on the biophysical properties of AMPA receptors, specifically on the homomeric GluA2 and the heteromeric GluA2/A3 subunits and assessed for inhibitory actions. …”