Fisher discriminant analysis is performed on data sets of typically developing (TD) individuals and data sets of autism spectrum disorder (ASD) individuals to produce a model that classifies TD individuals from ASD individuals. The ASD data sets include pre-treatment folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS) pathway metabolic profile data and post-treatment folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS) pathway metabolic profile data for patients receiving one or more ASD treatments. Changes in adaptive behavior are predicted by utilizing regression of changes in adaptive behavior and changes in biochemical measurements observed in the data sets. Thus, the system can be used to predict the effectiveness of a given course of treatment for an ASD patient based on measured metabolite data of that patient, or to predict the overall effectiveness of a clinical trial based on metabolite data for the trial participants.

Fisher discriminant analysis is performed on data sets of typically developing (TD) individuals and data sets of autism spectrum disorder (ASD) individuals to produce a model that classifies TD individuals from ASD individuals. The ASD data sets include pre-treatment folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS) pathway metabolic profile data and post-treatment folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS) pathway metabolic profile data for patients receiving one or more ASD treatments. Changes in adaptive behavior are predicted by utilizing regression of changes in adaptive behavior and changes in biochemical measurements observed in the data sets. Thus, the system can be used to predict the effectiveness of a given course of treatment for an ASD patient based on measured metabolite data of that patient, or to predict the overall effectiveness of a clinical trial based on metabolite data for the trial participants.

Secure data processing is described. Particular systems and methods involve enrollment units and methods, where the method includes obtaining an input data representing a raw data associated with a user, generating a template for the input data, and storing the template in an enrollment database, optionally with an identifier for the user. Other systems and method involve comparison or authentication units or methods, where the method involves obtaining templates corresponding to data sets to be compared, comparing the templates using a pre-defined comparison function to yield a similarity measure, and if the similarity measure meets a similarity criterion, determining that the data sets are from the same source. In the systems and methods, the templates are secure and noise tolerant templates configured to reveal limited features of the data set and to prevent reconstruction of the data set from the template.

In an example, high-dimensional data is projected to a multi-dimensional space to differentiate clusters of the high-dimensional data. A user selection of at least two of the clusters may be received and a plurality of dissimilar dimensions may be extracted from the at least two clusters. In addition, a user selected of a dissimilar dimension from the plurality of extracted dissimilar dimensions may be received. In response to receipt of the user selection of the dissimilar dimension from the plurality of dissimilar dimensions, a plurality of correlated dimensions to the dissimilar dimension may be determined. In addition, the plurality of dissimilar dimensions and the plurality of correlated dimensions may be displayed.

In an example, high-dimensional data is projected to a multi-dimensional space to differentiate clusters of the high-dimensional data. A user selection of at least two of the clusters may be received and a plurality of dissimilar dimensions may be extracted from the at least two clusters. In addition, a user selected of a dissimilar dimension from the plurality of extracted dissimilar dimensions may be received. In response to receipt of the user selection of the dissimilar dimension from the plurality of dissimilar dimensions, a plurality of correlated dimensions to the dissimilar dimension may be determined. In addition, the plurality of dissimilar dimensions and the plurality of correlated dimensions may be displayed.