Image 1_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Image 7_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 3_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Image 6_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 10_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Image 3_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Image 5_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 9_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 4_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 11_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Table 6_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).xlsx حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Image 2_Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.).tif حسب Zhu Yang (756364)

"…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …"

Supplemental Tables S1 and S2 for Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks حسب Diana Murray (16859046)

"…The integrated method has better performance and identifies more high-confidence interactions than any of the component methods. The AF3Complex algorithm was used to predict the structures of 374 PPIs with a large fraction having at least partially overlapping interfaces with PrePPI models of the same complex. …"

Identify different types of urban renewal implementations at streetscape scale حسب Xiaotong Wang (20852492)

"…Existing research primarily focuses on detecting pixel-level or object-level changes in urban physical space, often neglecting the semantic complexity inherent in urban renewal. …"

Identification of ferroptosis-related LncRNAs as potential targets for improving immunotherapy in glioblastoma حسب Zhaochen Wang (12176245)

"…<p>The effect of ferroptosis-related long non-coding RNAs (lncRNAs) in predicting immunotherapy response to glioblastoma (GBM) remains obscure. …"

AI Influence in the Educational Environment حسب Lev Radman (21381269)

"…The CSV file contains Likert-scale and categorical responses, with a separate README describing each variable and coding scheme.</p><p dir="ltr"><b>Potential reuse</b><br>Researchers can replicate or extend technology-acceptance models in emerging-economy contexts, compare student versus professional cohorts, or conduct secondary analyses on AI self-efficacy and algorithmic trust.…"

<b>R</b><b>esidual</b> <b>GCB-Net</b>: Residual Graph Convolutional Broad Network on Emotion Recognition حسب Qilin Li (535447)

"…It can accurately reflect the emotional changes of the human body by applying graphical-based algorithms or models. EEG signals are nonlinear signals. …"

Figure 8 from Prostate Cancer Progression Modeling Provides Insight into Dynamic Molecular Changes Associated with Progressive Disease States حسب Runpu Chen (14942572)

"…Each tumor sample was color-coded by its <i>ERG</i> fusion status inferred by the <i>ERG</i> gene expression level. …"

Table 1_Generating normative data from web-based administration of the Cambridge Neuropsychological Test Automated Battery using a Bayesian framework.docx حسب Elizabeth Wragg (19710640)

"…Traditional methods for deriving normative data typically require extremely large samples of healthy participants, stratifying test variation by pre-specified age groups and key demographic features (age, sex, education). …"

<b>A virtual tracer experiment to assess the temporal origin of root water uptake, evaporation, and </b><b>drainage</b> حسب Paolo Nasta (19710883)

"…</p><p dir="ltr"><a href="" target="_blank">Two open-source Matlab scripts are available in the zip-files. The PT.m Matlab code determines the drainage transit time based on the particle tracking algorithm, while the VTE.m Matlab code determines the drainage and RWU transit times and relative rainfall contributions to actual evaporation, actual transpiration, and drainage using isotope transport simulations in HYDRUS-1D</a>. …"