The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 30, 2024

Filed:

Aug. 26, 2019
Applicant:

Becton, Dickinson and Company, Franklin Lakes, NJ (US);

Inventors:

Stephen P. A. Fodor, Palo Alto, CA (US);

Glenn K. Fu, Dublin, CA (US);

Assignee:

Becton, Dickinson and Company, Franklin Lakes, NJ (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G16B 25/00 (2019.01); C12N 15/10 (2006.01); C12Q 1/6809 (2018.01); C12Q 1/6837 (2018.01); C12Q 1/6851 (2018.01); C12Q 1/686 (2018.01); C12Q 1/6869 (2018.01); C12Q 1/6874 (2018.01); C12Q 1/6876 (2018.01); G16B 25/10 (2019.01); G16B 25/20 (2019.01); G16B 30/00 (2019.01);
U.S. Cl.
CPC ...
C12Q 1/6874 (2013.01); C12N 15/1065 (2013.01); C12Q 1/6809 (2013.01); C12Q 1/6837 (2013.01); C12Q 1/6851 (2013.01); C12Q 1/686 (2013.01); C12Q 1/6869 (2013.01); C12Q 1/6876 (2013.01); G16B 25/00 (2019.02); G16B 25/20 (2019.02); G16B 30/00 (2019.02); G16B 25/10 (2019.02);
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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