Leland Stanford Junior University

Nigam H Shah

Juan Manuel Banda

Vladimir Polony

Alison Victoria Callahan

Russ B Altman

Yael Garten

Mark Musen

Adrien Coulet

Systems and methods for structuring unstructured data according to a data object structure that enables fast query look-ups across a variety of space and time dimensions. Furthermore, many embodiments optimize the storage of the data objects using a set of compression techniques that configure the data types used for the data objects based on properties of the stored data. Furthermore, many embodiments provide are able to service query look-up requests without having to deserialize data within the byte stream format as stored in memory by encoding information that provide memory locations for requested data, thereby allowing for the immediate retrieval of the data as it is stored in the persistent memory.

Systems and methods for cohort analysis using compressed data objects enabling fast memory lookups

Methods for developing an ontology of pharmacogenomics (PGx) relationships starting from a lexicon of key pharmacogenomic entities and a syntactic parse is described. The syntactic structure of PGx statements is used to systematically extract commonly occurring relationships and to map them to a common schema. In an embodiment, extracted relationships have a 70-87.7% precision and involve not only key PGx entities such as genes, drugs, and phenotypes (e.g., VKORC1, warfarin, clotting disorder), but also critical entities that are frequently modified by these key entities (e.g., VKORC1 polymorphism, warfarin response, clotting disorder treatment).

Method and system for extraction and normalization of relationships via ontology induction

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Menlo Park, CA, United States of America

Nigam H Shah