EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression

Improved Method for Linear B-Cell Epitope Prediction Using Antigen’s Primary Sequence

One of the major challenges in designing a peptide-based vaccine is the identification of antigenic regions in an antigen that can stimulate B-cell's response, also called B-cell epitopes. In the past, several methods have been developed for the prediction of conformational and linear (or continuous) B-cell epitopes. However, the existing methods for predicting linear B-cell epitopes are far fr...

QSRR Study of Organic Dyes by Multiple Linear Regression Method Based on Genetic Algorithm (GA–MLR

Quantitative structure-retention relationships (QSRRs) are used to correlate paper chromatographic retention factors of disperse dyes with theoretical molecular descriptors. A data set of 23 compounds with known RF values was used. The genetic algorithm-multiple linear regression analysis (GA-MLR) with three selected theoretical descriptors was obtained. The stability and predictability of the ...

Rapid B Cell Linear Epitope Mapping

Conformational epitopes are thought to form the majority of strong antibody binding epitopes on most proteins. However numerous conformational epitopes may also be recognizable as linear epitopes, although with lower affinity. Linear B cell epitopes typically vary from 5 to 20 amino acids in length. If the antibody-binding region of the protein is unknown, an overlapping peptide library can be ...

prediction of linear and conformational b cell epitope of her2 ecd for monoclonal antibody development using immunoinformatic methods

Some Modifications to Calculate Regression Coefficients in Multiple Linear Regression

In a multiple linear regression model, there are instances where one has to update the regression parameters. In such models as new data become available, by adding one row to the design matrix, the least-squares estimates for the parameters must be updated to reflect the impact of the new data. We will modify two existing methods of calculating regression coefficients in multiple linear regres...