US 2022/0068431 A1 · DECODING APPROACHES FOR PROTEIN IDENTIFICATION

Abstract

Methods and systems are provided for accurate and efficient identification and quantification of proteins. In an aspect, disclosed herein is a method for identifying a protein in a sample of unknown proteins, comprising receiving information of a plurality of empirical measurements performed on the unknown proteins; comparing the information of empirical measurements against a database comprising a plurality of protein sequences, each protein sequence corresponding to a candidate protein among a plurality of candidate proteins; and for each of one or more of the plurality of candidate proteins, generating a probability that the candidate protein generates the information of empirical measurements, a probability that the plurality of empirical measurements is not observed given that the candidate protein is present in the sample, or a probability that the candidate protein is present in the sample; based on the comparison of the information of empirical measurements against the database.

Claims29

Dependent claims

A method for training a probabilistic computational model, comprising:

(a) obtaining, by a computer, the probabilistic computational model, which probabilistic computational model comprises a set of binding probabilities corresponding to a set of affinity reagents configured to bind to a set of amino acids of a protein;
(b) contacting a training set of unknown proteins with the set of affinity reagents;
(c) obtaining a plurality of empirical measurements of the training set of unknown proteins, which plurality of empirical measurements comprises binding measurements of the set of affinity reagents to at least one of the training set of unknown proteins;
(d) determining, by the computer, an updated binding probability for at least one affinity reagent of the set of affinity reagents, based at least in part on empirical measurements for the at least one affinity reagent;
and
(e) repeating at least one iteration of (b), (c), and (d) to iteratively optimize the set of binding probabilities.

3 more elements

Dependencies are inferred from the claim text.

Decoding approaches for protein identification

Life of this patent

Decoding approaches for protein identification

Life of this patent

Abstract

Claims29