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US Patent 11908548 Training data generation for artificial intelligence-based sequencing

Patent 11908548 was granted and assigned to Illumina on February, 2024 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
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Patent attributes

Patent Applicant
Illumina
Illumina
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Current Assignee
Illumina
Illumina
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
119085480
Patent Inventor Names
Amirali Kia0
Anindita Dutta0
Dorna Kashefhaghighi0
Date of Patent
February 20, 2024
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Patent Application Number
178276120
Date Filed
May 27, 2022
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Patent Citations
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US Patent 7405281 Fluorescent nucleotide analogs and uses therefor
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US Patent 7427673 Labelled nucleotides
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US Patent 7541444 Modified nucleotides
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US Patent 7566537 Labelled nucleotides
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US Patent 7592435 Modified nucleosides and nucleotides and uses thereof
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US Patent 8182993 Methods and processes for calling bases in sequence by incorporation methods
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US Patent 8241573 Systems and devices for sequence by synthesis analysis
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US Patent 8392126 Method and system for determining the accuracy of DNA base identifications
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Patent Citations Received
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US Patent 11983916 Relocation method, mobile machine using the same, and computer readable storage medium
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Patent Primary Examiner
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Juan A Torres
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CPC Code
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G16B 30/00
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G16B 20/20
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G16B 30/10
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G06F 16/907
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G06F 16/58
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G06N 3/04
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G06N 3/08
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G06N 3/084
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Patent abstract

The technology disclosed relates to generating ground truth training data to train a neural network-based template generator for cluster metadata determination task. In particular, it relates to accessing sequencing images, obtaining, from a base caller, a base call classifying each subpixel in the sequencing images as one of four bases (A, C, T, and G), generating a cluster map that identifies clusters as disjointed regions of contiguous subpixels which share a substantially matching base call sequence, determining cluster metadata based on the disjointed regions in the cluster map, and using the cluster metadata to generate the ground truth training data for training the neural network-based template generator for the cluster metadata determination task.

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