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Mapping and Modification of Gene Network Endophenotypes

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Summary

The USPTO published patent application US20260100246A1 by Inari Agriculture Technology, Inc., disclosing a machine learning method for predicting endophenotypes of interacting partner genes. The method partitions endophenotype profiles into two sets, modifies one set to a desired level, and uses a trained ML model to predict resulting changes in the unmodified set. The invention enables targeted modification of gene networks to achieve desired agricultural traits.

What changed

The USPTO published patent application US20260100246A1 disclosing a machine learning method for predicting endophenotypes of interacting partner genes in agricultural applications. The method involves obtaining endophenotype profiles corresponding to a genotype, partitioning profiles into two sets, modifying one set to a desired level, and inputting both sets into a trained ML model to predict resulting changes in the second set.

Agricultural biotechnology companies developing gene editing or precision breeding solutions should review this application for potential prior art or licensing considerations. The method's focus on predicting phenotypic outcomes from targeted gene modifications could impact R&D strategies for crop improvement programs.

What to do next

  1. Monitor for patent grant or rejection notices
  2. Review claims for potential licensing opportunities

Archived snapshot

Apr 10, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Applications

MAPPING AND MODIFICATION OF GENE NETWORK ENDOPHENOTYPES

Application US20260100246A1 Kind: A1 Apr 09, 2026

Assignee

Inari Agriculture Technology, Inc.

Inventors

Ross Everett ALTMAN, Karl Anton Grothe KREMLING

Abstract

A method for predicting endophenotypes of interacting partner genes includes obtaining one or more endophenotype profiles corresponding to a genotype, partitioning the one or more endophenotype profiles into a first set of endophenotypes and a second set of endophenotypes, and receiving an input to modify the first set of endophenotypes to a desired level. The method thus includes inputting the modified first set of endophenotypes and unmodified second set of endophenotypes into a trained machine-learning model to obtain a prediction of an updated second set of endophenotypes. The updated second set of endophenotypes represents an updated version of the second set of endophenotypes after interacting with the modified subset of the first set of endophenotypes.

CPC Classifications

G16B 20/00 C12N 9/222 C12N 15/11 C12N 15/8213 G16B 40/20 C12N 2310/20

Filing Date

2023-06-23

Application No.

18877684

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Last updated

Classification

Agency
USPTO
Instrument
Notice
Legal weight
Non-binding
Stage
Final
Change scope
Minor
Document ID
US20260100246A1
Docket
18877684

Who this affects

Applies to
Agricultural firms Technology companies
Industry sector
3254.1 Biotechnology
Activity scope
Patent filing IP registration
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Artificial Intelligence Healthcare

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