The raw data for Fig 6. by Hongjoo An (21703199)

“…Luciferase assay and human and mouse brain multi-omics data show that, during the differentiation of OL precursor cells (OPCs) into OLs, the enhancer activity of Sox10-E1 does not change while that of Sox10-E2 decreases significantly. Chromatin interaction data indicate that the two <i>Sox10</i> enhancers lie close to the border of the <i>Sox10</i> topologically associating domain (TAD). …”

The raw data for S4 Fig. by Hongjoo An (21703199)

“…Luciferase assay and human and mouse brain multi-omics data show that, during the differentiation of OL precursor cells (OPCs) into OLs, the enhancer activity of Sox10-E1 does not change while that of Sox10-E2 decreases significantly. Chromatin interaction data indicate that the two <i>Sox10</i> enhancers lie close to the border of the <i>Sox10</i> topologically associating domain (TAD). …”

Functional Characterization of a Highly Efficient UDP-Glucosyltransferase CitUGT72AZ4 Involved in the Biosynthesis of Flavonoid Glycosides in Citrus by Bin Liao (714989)

“…Virus-induced gene silencing of <i>CitUGT72AZ4</i> significantly decreased the accumulation of flavonoid 4′-<i>O</i>-glucosides. …”

The raw data for Fig 5B. by Hongjoo An (21703199)

“…Luciferase assay and human and mouse brain multi-omics data show that, during the differentiation of OL precursor cells (OPCs) into OLs, the enhancer activity of Sox10-E1 does not change while that of Sox10-E2 decreases significantly. Chromatin interaction data indicate that the two <i>Sox10</i> enhancers lie close to the border of the <i>Sox10</i> topologically associating domain (TAD). …”

The raw data for Fig 8A. by Hongjoo An (21703199)

“…Luciferase assay and human and mouse brain multi-omics data show that, during the differentiation of OL precursor cells (OPCs) into OLs, the enhancer activity of Sox10-E1 does not change while that of Sox10-E2 decreases significantly. Chromatin interaction data indicate that the two <i>Sox10</i> enhancers lie close to the border of the <i>Sox10</i> topologically associating domain (TAD). …”

Establishment of a diabetic rat model. by Lan Zeng (638254)

“…The abnormal production and release of VEGF promote the proliferation and migration of endothelial cells (ECs), which are critical drivers of retinal neovascularization [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0312791#pone.0312791.ref019" target="_blank">19</a>]. Accordingly, we measured VEGF gene expression and found that it was significantly increased in the retinas of diabetic rats (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0312791#pone.0312791.g003" target="_blank">Fig 3A</a>). …”

Dynamics of EGFP and mRFP fluorescence in infected cells under different heat shock conditions. by Enrique Paz-Cortés (20988196)

Probability of Cost-Effectiveness Across CET. by Yiping An (20609789)

“…Scenario analyses conducted over a time horizon extending from 10 to 30 years showed that the ICER decreased significantly with longer follow-up, gradually approaching the 0.51GDP threshold and remaining below the 0.90 GDP threshold throughout the analysis.…”

Base-case analysis. by Yiping An (20609789)

“…Scenario analyses conducted over a time horizon extending from 10 to 30 years showed that the ICER decreased significantly with longer follow-up, gradually approaching the 0.51GDP threshold and remaining below the 0.90 GDP threshold throughout the analysis.…”

Complexity comparison of different models. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Dynamic window based median filtering algorithm. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Flow of operation of improved KMA. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Improved DAE based on LSTM. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Autoencoder structure. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Changes in rumen fluid metabolites. by Shiqi Zhang (709298)

Effect of alkali-stress to chlorophyll fluorescence parameters compared to control treatment. by Zeyu Jiang (5094320)

Effect of alkali-stress on photosynthetic pigments of hemp seedlings compared to control treatment. by Zeyu Jiang (5094320)

Effect of alkali-stress on physiological indices of antioxidant system compared to control treatment. by Zeyu Jiang (5094320)

The Fig illustrates the effects of mutations on the stability, flexibility, compactness, and interactions of the AKT2-Ipatasertib complex through molecular dynamics simulations. by Sadia Afrin Runa (22504971)

TAD analysis for <i>Sox10.</i> by Hongjoo An (21703199)