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

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

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

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

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

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

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

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

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

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

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

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The decrease in OD_320nm over time in spectrophotometric ATPase activity assays. by Kai-Yin Chau (18504230)

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>). …”

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)

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)

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

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Modifying pregnenolone to decrease its lipophilicity results in decreased cellular uptake. by Jeffrey M. McManus (7512926)

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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Transcriptional and translational markers of syncytialization and biochemical differentiation are significantly decreased by rotenone. by O’Llenecia S. Walker (8486163)

Genes whose expression was decreased by 100 nM ouabain by more than 1.3-fold. by Larisa V. Smolyaninova (3600053)