Patents by Inventor Nishant Bhat
Nishant Bhat has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11790282Abstract: Genetic-variant data is obtained that corresponds to one or more variants associated with a client. Each of the one or more variants corresponds to an instance of one or more bases positioned at one or more first positions in a first genetic sequence differ from corresponding one or more bases positioned in a reference genetic sequence. The first genetic sequence is a genetic sequence of the client. Sensor data is obtained that provides an indication of one or more characteristics of a current or past environment of the client. The genetic-variant data and the sensor data is processed to generate a disease-risk metric corresponding to a predicted risk of the client developing a particular disease. A communication is generated that is indicative of the disease-risk metric. The communication is transmitted to a remote device.Type: GrantFiled: May 11, 2022Date of Patent: October 17, 2023Assignee: Color Health, Inc.Inventors: Ryan Barrett, Nishant Bhat, Huy Hong, Katsuya Noguchi, Wendy McKennon, Krishna Pant, Taylor Sittler, Othman Laraki, Elad Gil
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Patent number: 11361842Abstract: Techniques are provided for detecting copy number variations. Each sequence read of a set of sequence reads is aligned with a portion of a reference sequence. A coverage vector is generated that includes a plurality of elements, each element in the plurality of elements indicating a number of the set of sequence reads that were aligned to a particular position within the reference sequence. A normalization vector is accessed that was generated based on performance of a component analysis on a set of other coverage vectors corresponding to a set of other subjects. An adjusted coverage vector is generated using the coverage vector and normalization vector. One or more subject-specific normalization values are generated based on the coverage vector. One or more copy number variations are identified that corresponding to the sample using the adjusted coverage vector and the subject-specific normalization values.Type: GrantFiled: August 4, 2021Date of Patent: June 14, 2022Assignee: Color Health, Inc.Inventors: Ryan Barrett, Nishant Bhat, Huy Hong, Katsuya Noguchi, Wendy McKennon, Krishna Pant, Taylor Sittler, Othman Laraki, Elad Gil
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Patent number: 11120369Abstract: Techniques, systems, and products for analyzing sparse indicators and sensor data and generating communications are disclosed. The sensors may be associated with or incorporated into devices that may automatically relay sensor data for use in analyses and communication generation.Type: GrantFiled: July 2, 2020Date of Patent: September 14, 2021Assignee: COLOR HEALTH, INC.Inventors: Ryan Barrett, Nishant Bhat, Huy Hong, Katsuya Noguchi, Wendy McKennon, Krishna Pant, Taylor Sittler, Othman Laraki, Elad Gil
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Patent number: 10853130Abstract: Embodiments in the disclosure are directed to the use of distributed computing to align reads against multiple portions of a reference dataset. Aligned portions of the reference dataset that correspond with an above-threshold alignment score can be assessed for the presence of sparse indicators that can be categorized and used to influence a determination of a state transition likelihood. Various tasks associated with the processing of reads (e.g., alignment, sparse indicator detection, and/or determination of a state transition likelihood) may be able to take advantage of parallel processing and can be distributed among the machines while considering the resource utilization of those machines. Different load-balancing mechanisms can be employed in order to achieve even resource utilization across the machines, and in some cases may involve assessing various processing characteristics that reflect a predicted resource expenditure and/or time profile for each task to be processed by a machine.Type: GrantFiled: September 19, 2017Date of Patent: December 1, 2020Assignee: Color Genomics, Inc.Inventors: Ryan Barrett, Taylor Sittler, Krishna Pant, Zhenghua Li, Katsuya Noguchi, Nishant Bhat, Othman Laraki, Jeroen Van den Akker, Kurt Smith
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Publication number: 20200334497Abstract: Techniques, systems, and products for analyzing sparse indicators and sensor data and generating communications are disclosed. The sensors may be associated with or incorporated into devices that may automatically relay sensor data for use in analyses and communication generation.Type: ApplicationFiled: July 2, 2020Publication date: October 22, 2020Applicant: Color Genomics, Inc.Inventors: Ryan Barrett, Nishant Bhat, Huy Hong, Katsuya Noguchi, Wendy McKennon, Krishna Pant, Taylor Sittler, Othman Laraki, Elad Gil
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Patent number: 10733476Abstract: Techniques, systems, and products for analyzing sparse indicators and sensor data and generating communications are disclosed. The sensors may be associated with or incorporated into devices that may automatically relay sensor data for use in analyses and communication generation.Type: GrantFiled: August 22, 2017Date of Patent: August 4, 2020Assignee: Color Genomics, Inc.Inventors: Ryan Barrett, Nishant Bhat, Huy Hong, Katsuya Noguchi, Wendy McKennon, Krishna Pant, Taylor Sittler, Othman Laraki, Elad Gil
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Patent number: 9811438Abstract: Methods and systems disclosed herein relate generally to data processing by applying machine learning techniques to iteration data to identify anomaly subsets of iteration data. More specifically, iteration data for individual iterations of a workflow involving a set of tasks may contain a client data set, client-associated sparse indicators and their classifications, and a set of processing times for the set of tasks performed in that iteration of the workflow. These individual iterations of the workflow may also be associated with particular data sources. Using the iteration data, anomaly subsets within the iteration data can be identified, such as data items resulting from systematic error associated with particular data sources, sets of sparse indicators to be validated or double-checked, or tasks that are associated with long processing times. The anomaly subsets can be provided in a generated communication or report in order to optimize future iterations of the workflow.Type: GrantFiled: May 11, 2017Date of Patent: November 7, 2017Assignee: COLOR GENOMICS, INC.Inventors: Ryan Barrett, Katsuya Noguchi, Nishant Bhat, Zhengua Li, Kurt Smith
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Patent number: 9813467Abstract: Techniques are disclosed for processing and aligning incomplete data. A stream of data is received from a data source including a plurality of reads. While receiving the stream of data and prior to having received all of the plurality of reads, a set of reads is extracted from the plurality of reads. Each of the set of reads is aligned to a corresponding portion of a reference data set. For each particular position of a plurality of particular positions of the reference data set, a subset of reads of the aligned set of reads is identified. A value of a client data set is generated based on the subset of reads. A variable is generated based on the client data set. Data is routed when a condition, based on the variable, is satisfied.Type: GrantFiled: March 7, 2017Date of Patent: November 7, 2017Assignee: COLOR GENOMICS, INC.Inventors: Ryan Barrett, Taylor Sittler, Krishna Pant, Zhenghua Li, Katsuya Noguchi, Nishant Bhat
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Patent number: 9774508Abstract: Techniques, systems, and products for analyzing sparse indicators and sensor data and generating communications are disclosed. The sensors may be associated with or incorporated into devices that may automatically relay sensor data for use in analyses and communication generation.Type: GrantFiled: January 13, 2017Date of Patent: September 26, 2017Assignee: COLOR GENOMICS, INC.Inventors: Ryan Barrett, Nishant Bhat, Huy Hong, Katsuya Noguchi, Wendy McKennon
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Patent number: 9678794Abstract: Methods and systems disclosed herein relate generally to data processing by applying machine learning techniques to iteration data to identify anomaly subsets of iteration data. More specifically, iteration data for individual iterations of a workflow involving a set of tasks may contain a client data set, client-associated sparse indicators and their classifications, and a set of processing times for the set of tasks performed in that iteration of the workflow. These individual iterations of the workflow may also be associated with particular data sources. Using the iteration data, anomaly subsets within the iteration data can be identified, such as data items resulting from systematic error associated with particular data sources, sets of sparse indicators to be validated or double-checked, or tasks that are associated with long processing times. The anomaly subsets can be provided in a generated communication or report in order to optimize future iterations of the workflow.Type: GrantFiled: December 1, 2016Date of Patent: June 13, 2017Assignee: COLOR GENOMICS, INC.Inventors: Ryan Barrett, Katsuya Noguchi, Nishant Bhat, Zhengua Li, Kurt Smith
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Publication number: 20170161105Abstract: Methods and systems disclosed herein relate generally to data processing by applying machine learning techniques to iteration data to identify anomaly subsets of iteration data. More specifically, iteration data for individual iterations of a workflow involving a set of tasks may contain a client data set, client-associated sparse indicators and their classifications, and a set of processing times for the set of tasks performed in that iteration of the workflow. These individual iterations of the workflow may also be associated with particular data sources. Using the iteration data, anomaly subsets within the iteration data can be identified, such as data items resulting from systematic error associated with particular data sources, sets of sparse indicators to be validated or double-checked, or tasks that are associated with long processing times. The anomaly subsets can be provided in a generated communication or report in order to optimize future iterations of the workflow.Type: ApplicationFiled: December 1, 2016Publication date: June 8, 2017Inventors: Ryan Barrett, Katsuya Noguchi, Nishant Bhat, Zhengua Li, Kurt Smith