San Francisco, CA, United States of America

Shannon Hateley

USPTO Granted Patents = 2 

Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2022-2024

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2 patents (USPTO):Explore Patents

Title: Innovations by Shannon Hateley in Genetic Research

Introduction

Shannon Hateley is an accomplished inventor based in San Francisco, CA. He has made significant contributions to the field of genetic research, particularly in the area of community assignments and genetic variant origination. With a total of 2 patents, his work has the potential to impact how individuals are classified within genetic communities.

Latest Patents

Hateley's latest patents focus on techniques for characterizing variants of interest and predicting assignments of individuals to communities based on genetic information. The first patent involves accessing DNA datasets of reference individuals to generate a cluster with additional individuals who share identity by descent (IBD) with these reference individuals. By analyzing genealogical data, the characterization of genetic variants is summarized based on statistical results. The second patent outlines a method for determining community membership by inputting haplotypes into a community-specific model, which is trained using samples that include haplotypes of reference individuals.

Career Highlights

Shannon Hateley is currently employed at Ancestry.com DNA, LLC, where he continues to innovate in the field of genetics. His work is instrumental in advancing the understanding of genetic relationships and community assignments.

Collaborations

Hateley collaborates with notable colleagues such as Jake Kelly Byrnes and Julie M Granka, who contribute to the research and development of genetic technologies.

Conclusion

Shannon Hateley's contributions to genetic research through his patents and work at Ancestry.com DNA, LLC highlight the importance of innovation in understanding genetic communities. His techniques for characterizing genetic variants and predicting community assignments are paving the way for future advancements in the field.

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