Expanse Networks, Inc.

23andme, Inc.

Expanse Bioinformatics, Inc.

Andrew Alexander Kenedy

Charles Anthony Eldering

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.

Computer implemented identification of genetic similarity

A method, software, database, and system in which a query attribute is used as the basis for accessing stored attribute combinations and their frequencies of occurrence for individuals; and tabulating, based on frequencies of occurrence, those attribute combinations that are most likely to co-occur with the query attribute.

Determination and display of likelihoods over time of developing age-associated disease

Comparison and identification of attribute similarity based on genetic markers

Attribute combination discovery for predisposition determination of health conditions

Computer implemented modeling and prediction of phenotypes

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.

Attribute identification based on seeded learning

Computer implemented predisposition prediction in a genetics platform

Computer implemented identification of modifiable attributes associated with phenotypic predispositions in a genetics platform

An embodiment may involve storing, by a computing device and in a database, a set of pangenetic attributes of a set of individuals, wherein the pangenetic attributes of the set are respectively and statistically associated with products; based on the statistical associations between the pangenetic attributes and the products, determining, by the computing device, product recommendations for a second set of individuals; receiving, by the computing device and from the second set of individuals, a plurality of measures of satisfaction with the product recommendations; based on the plurality of measures of satisfaction, learning, by the computing device, an association between a subset of the pangenetic attributes and a particular product; and storing, by the computing device and in the database, the learned association, wherein the learned association provides a basis for subsequent recommendations of the particular product when a subsequent individual exhibits the subset of the pangenetic attributes.

Learning system for pangenetic-based recommendations

A method, software, database and system for determining an optimal treatment for an illness in an individual and for determining the impact (e.g., side effects and intended benefits) of the treatment in the individual are presented in which an attribute profile of the individual containing genetic and non-genetic attributes is compared against a database containing combinations genetic and non-genetic attributes that are statistically associated with successful treatment of the illness in other individuals.

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Sugar Land, TX, United States of America

Andrew Alexander Kenedy