A system and method are presented in which known genetic attributes associated with a condition are used to seed the determination of additional attributes which are associated with the condition. Based on the learning, the additional attributes (genetic, behavioral, or both) provide for an increased correlation between the combined attributes and the condition. For behavioral attributes, a measure of the impact of the behavioral attribute on the risk of the condition can be transmitted to another device or system.

A system and method are presented in which known genetic attributes associated with a condition are used to seed the determination of additional attributes which are associated with the condition. Based on the learning, the additional attributes (genetic, behavioral, or both) provide for an increased correlation between the combined attributes and the condition. For behavioral attributes, a measure of the impact of the behavioral attribute on the risk of the condition can be transmitted to another device or system.

A method, software, database and system for attribute partner identification and social network based attribute analysis are presented in which attribute profiles associated with individuals can be compared and potential partners identified. Connections can be formed within social networks based on analysis of genetic and non-genetic data. Degrees of attribute separation (genetic and non-genetic) can be utilized to analyze relationships and to identify individuals who might benefit from being connected.

A method, software, database and system for attribute partner identification and social network based attribute analysis are presented in which attribute profiles associated with individuals can be compared and potential partners identified. Connections can be formed within social networks based on analysis of genetic and non-genetic data. Degrees of attribute separation (genetic and non-genetic) can be utilized to analyze relationships and to identify individuals who might benefit from being connected.

The present disclosure provides a novel integrated entropy-based method that combines genome-wide profiling and network analyses for diagnostic and prognostic applications. The present disclosure further provides the integration of multiomics datasets, network analyses and machine learning that enable predictions on diagnosing infectious diseases and predicting the probability that they will escape treatment/the host immune system and/or become antibiotic resistant. The present disclosure provides a primary gateway towards the development of highly accurate infectious disease prognostics.

Provided herein are methods for accurately determining the alleles present at a locus that is broadly applicable to any locus, including highly polymorphic loci such as HLA loci, BGA loci and HV loci. Embodiments of the disclosed methods are useful in a wide range of applications, including, for example, organ transplantation, personalized medicine, diagnostics, forensics and anthropology.

Provided herein are methods for accurately determining the alleles present at a locus that is broadly applicable to any locus, including highly polymorphic loci such as HLA loci, BGA loci and HV loci. Embodiments of the disclosed methods are useful in a wide range of applications, including, for example, organ transplantation, personalized medicine, diagnostics, forensics and anthropology.

Computer software products, methods, and systems are described which provide functionality to a user conducting experiments designed to detect and/or identify genetic sequences and other characteristics of a genetic sample, such as, for instance, gene copy number and aberrations thereof. The presently described software allows the user to interact with a graphical user interface which depicts the genetic information obtained from the experiment. The presently disclosed methods and software are related to bioinformatics and biological data analysis. Specifically, provided are methods, computer software products and systems for analyzing and visually depicting genotyping data on a screen or other visual projection. The presently disclosed methods and software allow the user conducting the experiment to differentially filter complex genetic data and information by varying genetic parameters and removing or highlighting visually various regions of genetic data of interest (CytoRegions). These differential filters may be applied by the user to the entire set of genetic data and/or only to the specific CytoRegions of interest.

A computer-implemented method of selecting one or more amino acid sequences for inclusion in a vaccine from a set of predicted immunogenic candidate amino acid sequences includes identifying an immune profile response value for each candidate amino acid sequence with respect to each one of a plurality of sample components of an immune profile. The immune profile response value represents whether the respective candidate amino acid sequence results in an immune response for the sample components of the immune profile. A plurality of immune profiles are retrieved for a population. A plurality of representative immune profiles are generated for the population. The representative immune profiles overlap with the sample components of the immune profiles. The one or more amino acid sequences for inclusion in the vaccine that minimises a likelihood of no immune response for each representative immune profile, based on the immune profile response values, are selected.

A computer-implemented method of selecting one or more amino acid sequences for inclusion in a vaccine from a set of predicted immunogenic candidate amino acid sequences includes identifying an immune profile response value for each candidate amino acid sequence with respect to each one of a plurality of sample components of an immune profile. The immune profile response value represents whether the respective candidate amino acid sequence results in an immune response for the sample components of the immune profile. A plurality of immune profiles are retrieved for a population. A plurality of representative immune profiles are generated for the population. The representative immune profiles overlap with the sample components of the immune profiles. The one or more amino acid sequences for inclusion in the vaccine that minimises a likelihood of no immune response for each representative immune profile, based on the immune profile response values, are selected.