biotinylated lectins concanavalin cona (Vector Laboratories)
Structured Review

Biotinylated Lectins Concanavalin Cona, supplied by Vector Laboratories, used in various techniques. Bioz Stars score: 94/100, based on 297 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/biotinylated+lectins+concanavalin+cona/pmc12019741-37-0-33?v=Vector+Laboratories
Average 94 stars, based on 297 article reviews
Images
1) Product Images from "Lipopolysaccharide Detection with Glycan-Specific Lectins—a Nonspecific Binding Approach Applied to Surface Plasmon Resonance"
Article Title: Lipopolysaccharide Detection with Glycan-Specific Lectins—a Nonspecific Binding Approach Applied to Surface Plasmon Resonance
Journal: ACS Omega
doi: 10.1021/acsomega.5c00867
Figure Legend Snippet: Lectin detection profiles. A total of 12 plasmon shift values, measured after 15 min of immobilization, were recorded for each lectin, with the average and standard deviation values represented by each band in the graph. Each lectin is used to create the LPS profiles for each bacterial species injected at 100 μg/mL, as well as a PBS buffer blank reference. The lectins chosen are Concanavalin (ConA), Glycine max agglutinin (SBA), Triticum vulgaris agglutinin (WGA), Dolichos biflorus agglutinin (DBA), Ulex europaeus agglutinin (UEA I), Ricinus communis agglutinin (RCA), and Arachis hypogea agglutinin (PNA). These lectins will be referred by their abbreviation for the next figures to avoid unnecessary length in the legend.
Techniques Used: Standard Deviation, Injection
Figure Legend Snippet: Feature importance coefficient. Each bar illustrates the mean importance coefficients for the 7 features associated with 7 lectins, calculated from 10 randomly selected train/test splits of the data set using a Random Forest model with 100 trees.
Techniques Used:
Figure Legend Snippet: Feature reduction for RF and SVM machine learning models. The best-performing lectin set from the combination of increasing number of lectins (1 to 7, from left to right) is used in a 10 repeated 3-fold cross-validation to determine the accuracy for each model. Significant differences are assessed with a t -test ( p > 0.05). An asterisk indicates a distribution with a statistically significant difference in performance compared to a distribution without it.
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Figure Legend Snippet: Classification Report for Different Profile Lengths with the SVM Model
Techniques Used:
Figure Legend Snippet: Classification Report for Different Profile Lengths with the RF Model
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