1 ap olfm4 Search Results


olfm4  (Proteintech)
94
Proteintech olfm4
Screening for Potential CRC Prognostic Signature. (A) Point plot showing the AUC values for each IGP. Differential colors represent differential N‐Glycoform. Differential size represents the number of values detected in 90 samples. (B) Boxplot illustrating the AUC for each glycoform. Differential colors represent differential N‐Glycoform. (C) Comparison of AUC values for glycoproteins versus non‐glycoproteins. (D) Top 10 glycoproteins with the highest number of IGPs. The color represents the average number of N‐glycan across all sites in each protein, with higher saturation representing a higher average. (E) ROC curve displaying the performance of multiple glycoproteins logistic regression modules in identifying CRC. Each red dot represents an independent ROC value for each protein. (F) ROC curve showing the results of constructing a random forest model using a combination of CLCA1 and <t>OLFM4.</t> Each red dot represents an independent ROC value for each protein. (G) ROC curve presenting the training results of a random forest model for CLCA1 and <t>OLFM4</t> using public data. Each red dot represents an independent ROC value for each protein. (H) ROC curve illustrating the testing results of a random forest model for CLCA1 and OLFM4 using public data. Each red dot represents an independent ROC value for each protein. (I) Multivariate survival analyses of IHC patients involved Cox regression analysis. The red line segments represent high risk and the blue color represents low risk.
Olfm4, supplied by Proteintech, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/1+ap+olfm4/OLFM4+Fusion+Protein/pmc12140321-279-3-6
Average 94 stars, based on 1 article reviews
olfm4 - by Bioz Stars, 2026-09
94/100 stars
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olfm4 staining  (Proteintech)
96
Proteintech olfm4 staining
Screening for Potential CRC Prognostic Signature. (A) Point plot showing the AUC values for each IGP. Differential colors represent differential N‐Glycoform. Differential size represents the number of values detected in 90 samples. (B) Boxplot illustrating the AUC for each glycoform. Differential colors represent differential N‐Glycoform. (C) Comparison of AUC values for glycoproteins versus non‐glycoproteins. (D) Top 10 glycoproteins with the highest number of IGPs. The color represents the average number of N‐glycan across all sites in each protein, with higher saturation representing a higher average. (E) ROC curve displaying the performance of multiple glycoproteins logistic regression modules in identifying CRC. Each red dot represents an independent ROC value for each protein. (F) ROC curve showing the results of constructing a random forest model using a combination of CLCA1 and <t>OLFM4.</t> Each red dot represents an independent ROC value for each protein. (G) ROC curve presenting the training results of a random forest model for CLCA1 and <t>OLFM4</t> using public data. Each red dot represents an independent ROC value for each protein. (H) ROC curve illustrating the testing results of a random forest model for CLCA1 and OLFM4 using public data. Each red dot represents an independent ROC value for each protein. (I) Multivariate survival analyses of IHC patients involved Cox regression analysis. The red line segments represent high risk and the blue color represents low risk.
Olfm4 Staining, supplied by Proteintech, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/1+ap+olfm4/PTPN5+Antibody/pm39146181-297-1-4
Average 96 stars, based on 1 article reviews
olfm4 staining - by Bioz Stars, 2026-09
96/100 stars
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lc3  (Proteintech)
96
Proteintech lc3
Screening for Potential CRC Prognostic Signature. (A) Point plot showing the AUC values for each IGP. Differential colors represent differential N‐Glycoform. Differential size represents the number of values detected in 90 samples. (B) Boxplot illustrating the AUC for each glycoform. Differential colors represent differential N‐Glycoform. (C) Comparison of AUC values for glycoproteins versus non‐glycoproteins. (D) Top 10 glycoproteins with the highest number of IGPs. The color represents the average number of N‐glycan across all sites in each protein, with higher saturation representing a higher average. (E) ROC curve displaying the performance of multiple glycoproteins logistic regression modules in identifying CRC. Each red dot represents an independent ROC value for each protein. (F) ROC curve showing the results of constructing a random forest model using a combination of CLCA1 and <t>OLFM4.</t> Each red dot represents an independent ROC value for each protein. (G) ROC curve presenting the training results of a random forest model for CLCA1 and <t>OLFM4</t> using public data. Each red dot represents an independent ROC value for each protein. (H) ROC curve illustrating the testing results of a random forest model for CLCA1 and OLFM4 using public data. Each red dot represents an independent ROC value for each protein. (I) Multivariate survival analyses of IHC patients involved Cox regression analysis. The red line segments represent high risk and the blue color represents low risk.
Lc3, supplied by Proteintech, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/1+ap+olfm4/CEL+Antibody/pm39075329-52-17-35
Average 96 stars, based on 1 article reviews
lc3 - by Bioz Stars, 2026-09
96/100 stars
  Buy from Supplier

Image Search Results


Screening for Potential CRC Prognostic Signature. (A) Point plot showing the AUC values for each IGP. Differential colors represent differential N‐Glycoform. Differential size represents the number of values detected in 90 samples. (B) Boxplot illustrating the AUC for each glycoform. Differential colors represent differential N‐Glycoform. (C) Comparison of AUC values for glycoproteins versus non‐glycoproteins. (D) Top 10 glycoproteins with the highest number of IGPs. The color represents the average number of N‐glycan across all sites in each protein, with higher saturation representing a higher average. (E) ROC curve displaying the performance of multiple glycoproteins logistic regression modules in identifying CRC. Each red dot represents an independent ROC value for each protein. (F) ROC curve showing the results of constructing a random forest model using a combination of CLCA1 and OLFM4. Each red dot represents an independent ROC value for each protein. (G) ROC curve presenting the training results of a random forest model for CLCA1 and OLFM4 using public data. Each red dot represents an independent ROC value for each protein. (H) ROC curve illustrating the testing results of a random forest model for CLCA1 and OLFM4 using public data. Each red dot represents an independent ROC value for each protein. (I) Multivariate survival analyses of IHC patients involved Cox regression analysis. The red line segments represent high risk and the blue color represents low risk.

Journal: Advanced Science

Article Title: Deciphering the Metabolic Impact and Clinical Relevance of N‐Glycosylation in Colorectal Cancer through Comprehensive Glycoproteomic Profiling

doi: 10.1002/advs.202415645

Figure Lengend Snippet: Screening for Potential CRC Prognostic Signature. (A) Point plot showing the AUC values for each IGP. Differential colors represent differential N‐Glycoform. Differential size represents the number of values detected in 90 samples. (B) Boxplot illustrating the AUC for each glycoform. Differential colors represent differential N‐Glycoform. (C) Comparison of AUC values for glycoproteins versus non‐glycoproteins. (D) Top 10 glycoproteins with the highest number of IGPs. The color represents the average number of N‐glycan across all sites in each protein, with higher saturation representing a higher average. (E) ROC curve displaying the performance of multiple glycoproteins logistic regression modules in identifying CRC. Each red dot represents an independent ROC value for each protein. (F) ROC curve showing the results of constructing a random forest model using a combination of CLCA1 and OLFM4. Each red dot represents an independent ROC value for each protein. (G) ROC curve presenting the training results of a random forest model for CLCA1 and OLFM4 using public data. Each red dot represents an independent ROC value for each protein. (H) ROC curve illustrating the testing results of a random forest model for CLCA1 and OLFM4 using public data. Each red dot represents an independent ROC value for each protein. (I) Multivariate survival analyses of IHC patients involved Cox regression analysis. The red line segments represent high risk and the blue color represents low risk.

Article Snippet: IHC staining of OLFM4 (1:1000, 28432‐1‐AP, Proteintech) and CLCA1 (1:100, A15041, Abcam) were performed on paraffin‐embedded human colorectal cancer tissue microarray (HColA180Su21, Shanghai Outdo Biotech Co. Ltd., Shanghai, China), as previously described.

Techniques: Comparison, Glycoproteomics