Table 6_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx by Peng Zhu (277243)

“…A modeling approach using 92 combinations of nine machine learning algorithms was applied, producing a predictive model with good performance. …”

Trx and Ldh regulate the metabolic state of MBγ lobes. by Nicholas Raun (20623862)

Data-Driven Design of Random Heteropolypeptides as Synthetic Polyclonal Antibodies by Haisen Zhou (13017532)

“…Liquid-phase electron microscopy revealed flexible, intrinsically disordered protein-like conformations and folding-upon-binding dynamics. …”

Data-Driven Design of Random Heteropolypeptides as Synthetic Polyclonal Antibodies by Haisen Zhou (13017532)

“…Liquid-phase electron microscopy revealed flexible, intrinsically disordered protein-like conformations and folding-upon-binding dynamics. …”

Data-Driven Design of Random Heteropolypeptides as Synthetic Polyclonal Antibodies by Haisen Zhou (13017532)

“…Liquid-phase electron microscopy revealed flexible, intrinsically disordered protein-like conformations and folding-upon-binding dynamics. …”

Table 2_Uncovering differential gene expression between mtRNA-positive and -negative osteosarcoma cells: implications beyond mitochondrial function.xlsx by Xiaoyuan Meng (22261234)

“…Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed using Metascape and WebGestalt. A protein–protein interaction (PPI) network was constructed through the STRING database and visualized with Cytoscape. …”

Table 1_Uncovering differential gene expression between mtRNA-positive and -negative osteosarcoma cells: implications beyond mitochondrial function.xlsx by Xiaoyuan Meng (22261234)

“…Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed using Metascape and WebGestalt. A protein–protein interaction (PPI) network was constructed through the STRING database and visualized with Cytoscape. …”

Table 3_Uncovering differential gene expression between mtRNA-positive and -negative osteosarcoma cells: implications beyond mitochondrial function.xlsx by Xiaoyuan Meng (22261234)

“…Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed using Metascape and WebGestalt. A protein–protein interaction (PPI) network was constructed through the STRING database and visualized with Cytoscape. …”

Table 6_Pain - related methylation driver genes affect the prognosis of pancreatic cancer patients by altering immune function and perineural infiltration.xlsx by Chencheng Zhang (6877691)

“…Next, in order to elucidate the underlying mechanisms, we conducted differential expression analysis, protein-protein interaction network analysis, functional enrichment analysis, and single-cell sequencing. …”

Table 2_Pain - related methylation driver genes affect the prognosis of pancreatic cancer patients by altering immune function and perineural infiltration.xlsx by Chencheng Zhang (6877691)

“…Next, in order to elucidate the underlying mechanisms, we conducted differential expression analysis, protein-protein interaction network analysis, functional enrichment analysis, and single-cell sequencing. …”

Table 3_Pain - related methylation driver genes affect the prognosis of pancreatic cancer patients by altering immune function and perineural infiltration.xlsx by Chencheng Zhang (6877691)

“…Next, in order to elucidate the underlying mechanisms, we conducted differential expression analysis, protein-protein interaction network analysis, functional enrichment analysis, and single-cell sequencing. …”

Table 1_Pain - related methylation driver genes affect the prognosis of pancreatic cancer patients by altering immune function and perineural infiltration.xlsx by Chencheng Zhang (6877691)

“…Next, in order to elucidate the underlying mechanisms, we conducted differential expression analysis, protein-protein interaction network analysis, functional enrichment analysis, and single-cell sequencing. …”

Table 4_Pain - related methylation driver genes affect the prognosis of pancreatic cancer patients by altering immune function and perineural infiltration.xlsx by Chencheng Zhang (6877691)

“…Next, in order to elucidate the underlying mechanisms, we conducted differential expression analysis, protein-protein interaction network analysis, functional enrichment analysis, and single-cell sequencing. …”

Table 5_Pain - related methylation driver genes affect the prognosis of pancreatic cancer patients by altering immune function and perineural infiltration.xlsx by Chencheng Zhang (6877691)

“…Next, in order to elucidate the underlying mechanisms, we conducted differential expression analysis, protein-protein interaction network analysis, functional enrichment analysis, and single-cell sequencing. …”

Table 4_Integrated cytomembrane proteomics identifies EpCAM/MGST1 as therapeutic targets in metastatic laryngeal carcinoma.xlsx by Suling Zhuang (21775925)

“…Potential immunotherapy targets were identified and prioritized using an in silico screening algorithm for cytomembrane proteome.</p>Results<p>The in silico screening algorithm for cytomembrane proteome led to the recognition of EpCAM and MGST1 as potential targets. …”

Table 5_Integrated cytomembrane proteomics identifies EpCAM/MGST1 as therapeutic targets in metastatic laryngeal carcinoma.xlsx by Suling Zhuang (21775925)

“…Potential immunotherapy targets were identified and prioritized using an in silico screening algorithm for cytomembrane proteome.</p>Results<p>The in silico screening algorithm for cytomembrane proteome led to the recognition of EpCAM and MGST1 as potential targets. …”

Table 2_Integrated cytomembrane proteomics identifies EpCAM/MGST1 as therapeutic targets in metastatic laryngeal carcinoma.docx by Suling Zhuang (21775925)

“…Potential immunotherapy targets were identified and prioritized using an in silico screening algorithm for cytomembrane proteome.</p>Results<p>The in silico screening algorithm for cytomembrane proteome led to the recognition of EpCAM and MGST1 as potential targets. …”

Table 6_Integrated cytomembrane proteomics identifies EpCAM/MGST1 as therapeutic targets in metastatic laryngeal carcinoma.xlsx by Suling Zhuang (21775925)

“…Potential immunotherapy targets were identified and prioritized using an in silico screening algorithm for cytomembrane proteome.</p>Results<p>The in silico screening algorithm for cytomembrane proteome led to the recognition of EpCAM and MGST1 as potential targets. …”

Table 1_Integrated cytomembrane proteomics identifies EpCAM/MGST1 as therapeutic targets in metastatic laryngeal carcinoma.docx by Suling Zhuang (21775925)

“…Potential immunotherapy targets were identified and prioritized using an in silico screening algorithm for cytomembrane proteome.</p>Results<p>The in silico screening algorithm for cytomembrane proteome led to the recognition of EpCAM and MGST1 as potential targets. …”

Table 3_Integrated cytomembrane proteomics identifies EpCAM/MGST1 as therapeutic targets in metastatic laryngeal carcinoma.xlsx by Suling Zhuang (21775925)

“…Potential immunotherapy targets were identified and prioritized using an in silico screening algorithm for cytomembrane proteome.</p>Results<p>The in silico screening algorithm for cytomembrane proteome led to the recognition of EpCAM and MGST1 as potential targets. …”