US 12,148,509 B2
Decoding approaches for protein identification
Sujal M. Patel, Seattle, WA (US); Parag Mallick, San Mateo, CA (US); and Jarrett D. Egertson, San Carlos, CA (US)
Assigned to NAUTILUS SUBSIDIARY, INC., Seattle, WA (US)
Filed by NAUTILUS SUBSIDIARY, INC., Seattle, WA (US)
Filed on Nov. 30, 2022, as Appl. No. 18/060,526.
Application 18/060,526 is a continuation of application No. 17/221,431, filed on Apr. 2, 2021, granted, now 11,545,234.
Application 17/221,431 is a continuation of application No. 16/534,174, filed on Aug. 7, 2019, granted, now 11,721,412.
Application 16/534,174 is a continuation of application No. PCT/US2018/067985, filed on Dec. 28, 2018.
Application PCT/US2018/067985 is a continuation in part of application No. PCT/US2018/056807, filed on Oct. 20, 2018.
Claims priority of provisional application 62/611,979, filed on Dec. 29, 2017.
Prior Publication US 2023/0117795 A1, Apr. 20, 2023
Int. Cl. G16B 5/20 (2019.01); G01N 27/26 (2006.01); G01N 27/60 (2006.01); G01N 27/72 (2006.01)
CPC G16B 5/20 (2019.02) [G01N 27/26 (2013.01); G01N 27/60 (2013.01); G01N 27/72 (2013.01)] 33 Claims
OG exemplary drawing
 
1. A method for identifying proteins in a sample and their position on a substrate, comprising:
providing a plurality of proteins attached to a substrate;
carrying out a series of affinity binding measurements by exposing the plurality of proteins attached to unique spatial addresses on the substrate to a series of tagged affinity reagents to produce an outcome set comprising positive binding outcomes and negative binding outcomes for the plurality of proteins with the tagged affinity reagents;
providing a database comprising a set of candidate proteins, and calculating for each candidate protein, a probability of observing a positive binding outcome or negative binding outcome with each of the tagged affinity reagents;
identifying the plurality of proteins attached to the substrate by determining with a computer, using the database, calculated probability, and the outcome set, a most probable candidate protein or most probable group of candidate proteins in the database corresponding to each of the proteins attached to the substrate; and
storing the identification of each protein in the plurality of proteins and its corresponding unique spatial address on the substrate to a computer memory to identify the proteins present in the sample.