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Title: Chemical amplification based on fluid partitioning

Abstract

A system for nucleic acid amplification of a sample comprises partitioning the sample into partitioned sections and performing PCR on the partitioned sections of the sample. Another embodiment of the invention provides a system for nucleic acid amplification and detection of a sample comprising partitioning the sample into partitioned sections, performing PCR on the partitioned sections of the sample, and detecting and analyzing the partitioned sections of the sample.

Inventors:
; ;
Issue Date:
Research Org.:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1860012
Patent Number(s):
RE48,788
Application Number:
16/115,187
Assignee:
Lawrence Livermore National Security, LLC (Livermore, CA)
DOE Contract Number:  
W-7405-ENG-48
Resource Type:
Patent
Resource Relation:
Patent File Date: 08/28/2018
Country of Publication:
United States
Language:
English

Citation Formats

Anderson, Brian L., Colston, Bill W., and Elkin, Christopher J. Chemical amplification based on fluid partitioning. United States: N. p., 2021. Web.
Anderson, Brian L., Colston, Bill W., & Elkin, Christopher J. Chemical amplification based on fluid partitioning. United States.
Anderson, Brian L., Colston, Bill W., and Elkin, Christopher J. Tue . "Chemical amplification based on fluid partitioning". United States. https://www.osti.gov/servlets/purl/1860012.
@article{osti_1860012,
title = {Chemical amplification based on fluid partitioning},
author = {Anderson, Brian L. and Colston, Bill W. and Elkin, Christopher J.},
abstractNote = {A system for nucleic acid amplification of a sample comprises partitioning the sample into partitioned sections and performing PCR on the partitioned sections of the sample. Another embodiment of the invention provides a system for nucleic acid amplification and detection of a sample comprising partitioning the sample into partitioned sections, performing PCR on the partitioned sections of the sample, and detecting and analyzing the partitioned sections of the sample.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2021},
month = {10}
}

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