Multivariate analysis software "SIMCA"

On February 16th (15:00–15:30), we will hold an advanced webinar on "Multivariate Analysis Software: SIMCA" focusing on regression models (OPLS). SIMCA is a multivariate analysis software that is well-regarded in research, development, and manufacturing for its capabilities in overview, regression, discrimination, and classification. In this webinar, we will focus on 'Regression: OPLS' and include short demonstrations and case studies (three examples are planned). ● OPLS: Orthogonal Partial Least Squares An advanced model of PLS. By rotating so that the Y variable becomes the first axis, it facilitates interpretation and allows for prediction of the target variable and factor analysis. Example of OPLS usage: * Set the coffee quality evaluation score as the target variable and find the factors that contribute most from the metabolic profile's GC/MS data, aiming to predict the quality evaluation score. * While PLS was able to identify the most contributing factors, it was difficult to determine the second and third contributing factors, which could be found using OPLS. * Participation from competitors in the same industry is not allowed. * Please install the latest version of ZOOM.

An advanced webinar on "Multivariate Analysis Software: SIMCA" (Regression Model OPLS) will be held on September 26, 2025, from 15:00 to 15:30. SIMCA is a multivariate analysis software that is well-regarded in fields handling large data sets, offering features for overview, regression, discrimination, and classification. In this webinar, we will focus on 'Regression: OPLS' and include short demonstrations and case studies (three are planned). ● OPLS: Orthogonal Partial Least Squares A superior model to PLS. By rotating so that the Y variable becomes the first axis, interpretation is made easier. This model allows for the prediction of target variables and factor analysis. Example of OPLS usage: * Set the coffee quality evaluation score as the target variable, find the factors that contribute most from the metabolic profile GC/MS data, and further predict the quality evaluation score from the GC/MS data. * While PLS was able to identify the most contributing factors, determining the second and third most contributing factors was difficult. In contrast, OPLS made this identification easy.

On October 30th (15:00 to 15:30), we will hold an advanced webinar on "Multivariate Analysis Software: SIMCA" focusing on the discriminant model OPLS-DA. SIMCA is widely used in research and development settings that handle large data sets. In this webinar, we will focus on "Discrimination: OPLS-DA" and include demonstrations and case studies. ● OPLS-DA An enhanced model of PLS-DA. By rotating the axes to maximize the separation between classes, it makes discrimination between classes easier. Additionally, by utilizing the S-plot, reliable marker candidates that are difficult to identify from the loading plot can be visualized instantly. For example: * I want to explore biomarker candidates from case-control data. * I am struggling to find significant features as the T-test only reveals false positive-like factors. 【Registration】 Please register at https://form.k3r.jp/infocom_science/251030_SIMCA_webinar_a_OPLSDA. * Participation from competitors in the same industry is not allowed. * Please ensure you have the latest version of ZOOM installed.

We will be exhibiting at the 19th Metabolome Symposium. Please be sure to stop by our booth when you attend.