Abstract: Systems that facilitate immunogen design are described herein. An optimization component is provided to determine an immunogen according to at least one criterion. The immunogen comprises a set of overlapping sequences comprising sequences that are known to be and/or are likely to be immunogenic. At least one of the sequences that are likely to be immunogenic can be determined by analyzing associations between a host and a pathogen at a population level. Methods of determining an epitome are described herein. A plurality of sequences are received. At least one of the sequences is predicted to be an epitope based on a relationship between a diverse trait of a population and a mutation of a pathogen. A collection of the plurality of sequences is optimized according to one or more criteria to determine the epitome. Epitomes and immunogens determined by the systems and methods described herein are also contemplated.

Abstract: A system comprising a machine learning classifier trained on a plurality of associations between a host and a pathogen to predict a pathogen characteristic is described herein. The pathogen characteristic can relate to a disease state of the host. Computer-executable instructions for performing a method of forecasting a portion of a target molecule anticipated to influence an organism's condition also are described herein. The method comprises employing population data to automatically analyze one or more areas of the target molecule to determine the portion of the target molecule anticipated to influence the organism's condition. The population data can pertain to at least one relationship between at least one diverse organism trait and the target molecule. One or more epitopes forecast by employing the method also are contemplated.