University of Arizona authors' scholarly works published and cited works year 2020 from OpenAlex by Yan Han (11106597)

“…</li><li><b>Data Retrieval:</b> The process involves using the oa_fetch function from the openalexR package with the entity="works" parameter and specifying the institutions.ror.…”

Image 3_The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target.tif by Yunpeng Zou (3723007)

“…PLEK was further validated by qRT-PCR and Western blot in OS samples, and its function assessed via siRNA knockdown in macrophages within TME co-cultured with OS cells. …”

Image 2_The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target.tif by Yunpeng Zou (3723007)

“…PLEK was further validated by qRT-PCR and Western blot in OS samples, and its function assessed via siRNA knockdown in macrophages within TME co-cultured with OS cells. …”

Image 4_The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target.tif by Yunpeng Zou (3723007)

“…PLEK was further validated by qRT-PCR and Western blot in OS samples, and its function assessed via siRNA knockdown in macrophages within TME co-cultured with OS cells. …”

Image 5_The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target.tif by Yunpeng Zou (3723007)

“…PLEK was further validated by qRT-PCR and Western blot in OS samples, and its function assessed via siRNA knockdown in macrophages within TME co-cultured with OS cells. …”

Image 1_The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target.tif by Yunpeng Zou (3723007)

“…PLEK was further validated by qRT-PCR and Western blot in OS samples, and its function assessed via siRNA knockdown in macrophages within TME co-cultured with OS cells. …”

Data Sheet 1_The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target.zip by Yunpeng Zou (3723007)

“…PLEK was further validated by qRT-PCR and Western blot in OS samples, and its function assessed via siRNA knockdown in macrophages within TME co-cultured with OS cells. …”

Data Sheet 2_The osteosarcoma immune microenvironment in progression: PLEK as a prognostic biomarker and therapeutic target.pdf by Yunpeng Zou (3723007)

“…PLEK was further validated by qRT-PCR and Western blot in OS samples, and its function assessed via siRNA knockdown in macrophages within TME co-cultured with OS cells. …”

<b>Road intersections Data with branch information extracted from OSM</b> & <b>C</b><b>odes to implement the extraction </b>&<b> I</b><b>nstructions on how to </b><b>reproduce each... by Zihao Tang (19794537)

“…</li><li><b>utils_g.py</b>: Provides utility functions that assist in geometric operations and template matching processes.…”

DataSheet1_Application of a risk score model based on glycosylation-related genes in the prognosis and treatment of patients with low-grade glioma.docx by Binbin Zou (11358315)

“…Their potential roles within the LGG microenvironment are also not well understood.…”

Data Sheet 1_PLK2 as a key regulator of glycolysis and immune dysregulation in polycystic ovary syndrome.docx by Hua Ma (2443177)

“…Immune infiltration was assessed using CIBERSORT, ESTIMATE, and ssGSEA algorithms. Functional enrichment analysis (GO, KEGG, and Hallmark) was performed to annotate PLK2-related pathways. …”

Table 12_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…</p>Results<p>Through machine learning algorithms, RPL14, SMARCD3, and TCN1 were identified as candidate biomarkers. …”

Table 9_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…</p>Results<p>Through machine learning algorithms, RPL14, SMARCD3, and TCN1 were identified as candidate biomarkers. …”

Table 8_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…</p>Results<p>Through machine learning algorithms, RPL14, SMARCD3, and TCN1 were identified as candidate biomarkers. …”

Table 1_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…</p>Results<p>Through machine learning algorithms, RPL14, SMARCD3, and TCN1 were identified as candidate biomarkers. …”

Table 2_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…</p>Results<p>Through machine learning algorithms, RPL14, SMARCD3, and TCN1 were identified as candidate biomarkers. …”

Table 3_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.xlsx by Ting Wu (106368)

“…</p>Results<p>Through machine learning algorithms, RPL14, SMARCD3, and TCN1 were identified as candidate biomarkers. …”

Table 5_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.doc by Ting Wu (106368)

“…</p>Results<p>Through machine learning algorithms, RPL14, SMARCD3, and TCN1 were identified as candidate biomarkers. …”

Table 13_Decoding immune-metabolic crosstalk in ARDS: a transcriptomic exploration of biomarkers, cellular dynamics, and therapeutic pathways.doc by Ting Wu (106368)

“…</p>Results<p>Through machine learning algorithms, RPL14, SMARCD3, and TCN1 were identified as candidate biomarkers. …”

Data Sheet 1_Development of machine learning models for predicting postoperative hyperglycemia in non-diabetic gastric cancer patients: a retrospective cohort study analysis.pdf by Nan Wang (21935)

“…The primary outcome was POH, defined as a fasting venous plasma glucose level ≥ 7.8 mmol/L within 24 hours post-surgery. Nine machine learning algorithms, including Support Vector Machine with a radial basis function kernel (SVM-radial), Random Forest, XGBoost, and Logistic Regression, were developed and compared. …”