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US Patent 10047394 Digital counting of individual molecules by stochastic attachment of diverse labels

Patent 10047394 was granted and assigned to Cellular Research on August, 2018 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Cellular Research
Cellular Research
Current Assignee
Cellular Research
Cellular Research
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10047394
Date of Patent
August 14, 2018
Patent Application Number
15224460
Date Filed
July 29, 2016
Patent Citations Received
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US Patent 12071617 Hybrid targeted and whole transcriptome amplification
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US Patent 11467157 Measurement of protein expression using reagents with barcoded oligonucleotide sequences
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US Patent 11492660 Selective extension in single cell whole transcriptome analysis
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US Patent 11999949 Methods for targeted genomic analysis
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US Patent 12060607 Digital counting of individual molecules by stochastic attachment of diverse labels
0
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US Patent 11460468 Measurement of protein expression using reagents with barcoded oligonucleotide sequences
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US Patent 10202646 Digital counting of individual molecules by stochastic attachment of diverse labels
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US Patent 10208356 Massively parallel single cell analysis
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Patent Primary Examiner
‌
Channing S Mahatan
Patent abstract

Compositions, methods and kits are disclosed for high-sensitivity single molecule digital counting by the stochastic labeling of a collection of identical molecules by attachment of a diverse set of labels. Each copy of a molecule randomly chooses from a non-depleting reservoir of diverse labels. Detection may be by a variety of methods including hybridization based or sequencing. Molecules that would otherwise be identical in information content can be labeled to create a separately detectable product that is unique or approximately unique in a collection. This stochastic transformation relaxes the problem of counting molecules from one of locating and identifying identical molecules to a series of binary digital questions detecting whether preprogrammed labels are present. The methods may be used, for example, to estimate the number of separate molecules of a given type or types within a sample.

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