US 2023/0142596 A1 · IMMUNE RESPONSE PREDICTION FROM SPATIAL TRANSCRIPTOME

Abstract

Single cell ribonucleic acid sequencing data has provided numerous avenues to monitor and study organism more thoroughly at a cellular level, including spatial arrangement of cells. An approach to predicting cellular immune response based on cellular spatial features may be presented herein. The approach may include utilizing ribonucleic acid sequence data for a single cell (“scRNA-seq”) or cell from a tissue. The approach may also include extracting spatial features of the single cell using the scRNA-seq data including cell-to-cell interactions and relative distance between cells. The approach may include predicting an immune response of a cell or cells based on the extracted spatial features.

Claims20

Dependent claims

A computer-implemented method for predicting a cellular level immune response, the computer-implemented method comprising:

receiving, by a processor, a single cell ribonuclease sequence (“scRNA-seq”);
extracting, by the processor, spatial features of the single cell based, at least in part, on the scRNA-seq;
and
predicting, by the processor, an immune response based, at least in part, on the extracted spatial features.

1 more element

A computer system for predicting a cellular level immune response, the system comprising:

one or more computer processors;
one or more computer readable storage media;
and
computer program instructions to:
receive a single cell ribonuclease sequence (“scRNA-seq”);
extract spatial features of the single cell based, at least in part, on the scRNA-seq;
and
predict an immune response based, at least in part, on the extracted spatial features.

5 more elements

A computer program product for predicting a cellular level immune response, the computer program product comprising one or more computer readable storage device and program instructions sorted on the one or more computer readable storage device to:

receive a single cell ribonuclease sequence (“scRNA-seq”);
extract spatial features of the single cell based, at least in part, on the scRNA-seq;
and
predict an immune response based, at least in part, on the extracted spatial features.

1 more element

Dependencies are inferred from the claim text.

Facts

Application

17/522,054Filed 9 Nov 2021

Published

11 May 2023

Term ends

Not estimatedThe source records don’t support an estimate.

Classification10 codes

G16B 40/20
ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge…:…
G16H 50/20
ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or…: for…
G16B 5/00
Ict specially adapted for modelling or simulations in systems biology
G16B 15/00
Ict specially adapted for analysing two-dimensional [2d] or three-dimensional [3d] molecular structures

Immune response prediction from spatial transcriptome

Life of this patent

Immune response prediction from spatial transcriptome

Life of this patent

Abstract

Claims20