BatchMatch is an analysis software package for evaluating and removing batch effect based on Systems Analytics’ proprietary technology with US and international patents pending. It facilitates the combination and study of datasets with multiple batches and enhances the statistical confidence in detecting real biological signals.
With the use of BatchMatch, the ability to identify reproducible differentially expressed features and to develop accurate and robust predictive models for unknown samples can be significantly increased. Read more...
RAMP (Robust Accurate Modeling Protocol)
Class prediction is one of the most important goals in microarray gene expression data analysis. Successful class prediction is an important indication, not only of the importance of selected markers, but also of the robustness of the entire modeling process. Despite the fact that many publications report very high prediction performance, there has been a widespread lack of emphasis on robustness, reproducibility, and model generalization.
RAMP (Robust Accurate Modeling Protocol) is a predictive model construction package developed by Systems Analytics Inc. It is a software product for optimal and automatic construction of accurate, robust, and biologically relevant models for the prediction of control/treatment outcomes using microarray gene expression data. Read more...
TopBioMarkers® is a desktop application for analyzing genomic, proteomic and metabolomic expression profiling data, a software for the identification of robust and accurate biomarkers. It applies and integrates well-known feature selection methods and classification algorithms through a scheme that includes consensus voting, feature list reproducibility evaluation, and classification accuracy evaluation. The software can be applied to both two-class and multiple-class problems.
The software can greatly improve the robustness and reliability of the differentially expressed features selected, overcome the often encountered over-training or over-fitting problem of using them for developing predictive models. Read more...