Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by Robert Zomer (12796235)

“…Version 3.0 has been deprecated due to the discovery of a data inconsistency in the calculation of net longwave radiation in the source code used to generate the dataset. …”

Additional file 1 of The origin and evolution of cultivated rice and genomic signatures of heterosis for yield traits in super-hybrid rice by Yiyong Zhao (21466062)

“…Each gene's expression data is associated with a specific tissue sample, using a naming convention that includes the gene identifier, variety code, and tissue type, separated by underscores. …”

CIAHS-Data.xls by Yingchang Li (22195585)

“…For this purpose, we employed the Natural Breaks classification method to reclassify factor values. This method identifies inherent natural grouping points within the data through the Jenks optimization algorithm, maximizing between-class differences while minimizing within-class differences37. …”

Cell type classification in the 9-dpg leaves. by Frances K. Clark (5617169)

“…Associated with <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003469#pbio.3003469.s010" target="_blank">S10 Fig</a>. The code and data associated with this figure can be found at Open Science Framework (osf.io), <a href="https://doi.org/10.17605/OSF.IO/RFCWS" target="_blank">https://doi.org/10.17605/OSF.IO/RFCWS</a>.…”

Cell type classification in the leaf and sepal. by Frances K. Clark (5617169)

“…See also <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003469#pbio.3003469.s009" target="_blank">S9</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003469#pbio.3003469.s011" target="_blank">S11 Figs</a>. The code and data associated with this figure can be found at Open Science Framework (osf.io), <a href="https://doi.org/10.17605/OSF.IO/RFCWS" target="_blank">https://doi.org/10.17605/OSF.IO/RFCWS</a>.…”

Flexible Tail of Antimicrobial Peptide PGLa Facilitates Water Pore Formation in Membranes by Chunsuo Tian (20606534)

“…Using a deep learning-based key intermediate identification algorithm, we found that the C-terminal tail plays a crucial role for PGLa insertion into the membrane, and that with its assistance, a variety of water pores formed inside the membrane. …”

Table 10_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine le... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Table 6_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine lea... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Table 8_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine lea... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Table 2_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine lea... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Table 3_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine lea... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Table 7_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine lea... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Table 11_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine le... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Table 9_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine lea... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Table 4_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine lea... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Table 5_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine lea... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Table 1_Analysis of immune characteristics and inflammatory mechanisms in COPD patients: a multi-layered study combining bulk and single-cell transcriptome analysis and machine lea... by Changjin Wei (21751352)

“…Inflammatory-related COPD feature genes were selected using Lasso regression and random forest algorithms, and a COPD risk prediction model was constructed. …”

Image 3_Integrated single-cell and bulk RNA dequencing to identify and validate prognostic genes related to T Cell senescence in acute myeloid leukemia.tif by Mengyao Sha (15775124)

“…Prognostic genes showed strong binding activity to target drugs (IGF1R and ABT737). …”

Image 2_Integrated single-cell and bulk RNA dequencing to identify and validate prognostic genes related to T Cell senescence in acute myeloid leukemia.tif by Mengyao Sha (15775124)

“…Prognostic genes showed strong binding activity to target drugs (IGF1R and ABT737). …”

Table 4_Integrated single-cell and bulk RNA dequencing to identify and validate prognostic genes related to T Cell senescence in acute myeloid leukemia.csv by Mengyao Sha (15775124)

“…Prognostic genes showed strong binding activity to target drugs (IGF1R and ABT737). …”