US 2026/0229049 A1 · GENERATING SEPARABILITY AND DISJOINTNESS MEASURES FOR PAIRWISE INTERACTION DETECTION AND ACTIVE LEARNING

Abstract

The present disclosure relates to systems, non-transitory computer-readable media, and methods that implement a framework for determining measures of biological activity for pairwise interactions. Indeed, in one or more implementations, the disclosed systems generate a first set of individual perturbation representations from a first set of cells exposed to a first perturbation and a second set of individual perturbation representations, from a second set of cells exposed to a second perturbation. For instance, the disclosed systems combine the first individual perturbation representation and the second individual perturbation representation to determine a predicted pairwise representation. Moreover, in some instances, the disclosed systems generate a pairwise representation from a group of cells exposed to both the first and second perturbation. Additionally, from comparing the predicted pairwise representation with the pairwise representation, the disclosed systems generate a measure of biological activity of the first and second perturbation.

Claims20

Dependent claims

A computer-implemented method comprising:

generating a first set of individual perturbation representations of a first set of cells exposed to a first perturbation;
generating a second set of individual perturbation representations of a second set of cells exposed to a second perturbation;
additively combining the first set of individual perturbation representations and the second set of individual perturbation representations to generate a synthetic pairwise perturbation distribution;
generating an observed pairwise representation distribution from a third set of representations of a third set of cells exposed to both the first perturbation and the second perturbation;
and
determining a domain disjointedness measure between the first perturbation and the second perturbation by comparing the observed pairwise representation distribution and the synthetic pairwise perturbation distribution.

3 more elements

A system comprising:

at least one processor;
and
at least one non-transitory computer-readable storage medium storing instructions that, when executed by the at least one processor, cause the system to:
generate a first set of individual perturbation representations of a first set of cells exposed to a first perturbation;
generate a second set of individual perturbation representations of a second set of cells exposed to a second perturbation;
additively combine the first set of individual perturbation representations and the second set of individual perturbation representations to generate a synthetic pairwise perturbation distribution;
generate an observed pairwise representation distribution from a third set of representations of a third set of cells exposed to both the first perturbation and the second perturbation;
and
determine a domain disjointedness measure between the first perturbation and the second perturbation by comparing the observed pairwise representation distribution and the synthetic pairwise perturbation distribution.

6 more elements

A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause a computing device to:

generate a first set of individual perturbation representations of a first set of cells exposed to a first perturbation;
generate a second set of individual perturbation representations of a second set of cells exposed to a second perturbation;
additively combine the first set of individual perturbation representations and the second set of individual perturbation representations to generate a synthetic pairwise perturbation distribution;
generate an observed pairwise representation distribution from a third set of representations of a third set of cells exposed to both the first perturbation and the second perturbation;
and
determine a domain disjointedness measure between the first perturbation and the second perturbation by comparing the observed pairwise representation distribution and the synthetic pairwise perturbation distribution.

3 more elements

Dependencies are inferred from the claim text.

Generating separability and disjointness measures for pairwise interaction detection and active learning

Life of this patent

Generating separability and disjointness measures for pairwise interaction detection and active learning

Life of this patent

Abstract

Claims20