Patents by Inventor Boris Shpak
Boris Shpak has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20230178178Abstract: Techniques for determining one or more cell composition percentages from expression data. The techniques include obtaining expression data for a biological sample, the biological sample previously obtained from a subject, the expression data including first expression data associated with a first set of genes associated with a first cell type; determining a first cell composition percentage for the first cell type using the expression data and one or more non-linear regression models including a first non-linear regression model, wherein the first cell composition percentage indicates an estimated percentage of cells of the first cell type in the biological sample, wherein determining the first cell composition percentage for the first cell type comprises: processing the first expression data with the first non-linear regression model to determine the first cell composition percentage for the first cell type; and outputting the first cell composition percentage.Type: ApplicationFiled: December 15, 2022Publication date: June 8, 2023Applicant: BostonGene CorporationInventors: Aleksandr Zaitsev, Maksim Chelushkin, Ilya Cheremushkin, Ekaterina Nuzhdina, Vladimir Zyrin, Daniiar Dyikanov, Alexander Bagaev, Ravshan Ataullakhanov, Boris Shpak
-
Patent number: 11587642Abstract: Techniques for determining one or more cell composition percentages from expression data. The techniques include obtaining expression data for a biological sample, the biological sample previously obtained from a subject, the expression data including first expression data associated with a first set of genes associated with a first cell type; determining a first cell composition percentage for the first cell type using the expression data and one or more non-linear regression models including a first non-linear regression model, wherein the first cell composition percentage indicates an estimated percentage of cells of the first cell type in the biological sample, wherein determining the first cell composition percentage for the first cell type comprises: processing the first expression data with the first non-linear regression model to determine the first cell composition percentage for the first cell type; and outputting the first cell composition percentage.Type: GrantFiled: March 29, 2022Date of Patent: February 21, 2023Assignee: BostonGene CorporationInventors: Aleksandr Zaitsev, Maksim Chelushkin, Ilya Cheremushkin, Ekaterina Nuzhdina, Vladimir Zyrin, Daniiar Dyikanov, Alexander Bagaev, Ravshan Ataullakhanov, Boris Shpak
-
Publication number: 20220372580Abstract: Techniques for using machine learning to estimate tumor expression levels of genes in tumor cells. The techniques include obtaining expression data for a set of genes comprising a first plurality of genes associated with the tumor cells and a second plurality of genes associated with tumor microenvironment cells; determining the tumor expression levels of the first plurality of genes in the tumor cells using a plurality of machine learning models, the determining comprising: generating a first set of features for the first gene; providing the first set of features as input to the first machine learning model to obtain an output comprising a tumor microenvironment expression level estimate of the first gene in the tumor microenvironment cells; and determining a first tumor expression level for the first gene in the tumor cells using the output of the first machine learning model and a total expression level for the first gene.Type: ApplicationFiled: April 29, 2022Publication date: November 24, 2022Applicant: BostonGene CorporationInventors: Aleksandr Zaitsev, Alexander Bagaev, Maksim Chelushkin, Valentina Beliaeva, Boris Shpak, Daniiar Dyikanov, Anastasia Zotova, Michael F. Goldberg, Cagdas Tazearslan
-
Publication number: 20220230707Abstract: Techniques for determining one or more cell composition percentages from expression data. The techniques include obtaining expression data for a biological sample, the biological sample previously obtained from a subject, the expression data including first expression data associated with a first set of genes associated with a first cell type; determining a first cell composition percentage for the first cell type using the expression data and one or more non-linear regression models including a first non-linear regression model, wherein the first cell composition percentage indicates an estimated percentage of cells of the first cell type in the biological sample, wherein determining the first cell composition percentage for the first cell type comprises: processing the first expression data with the first non-linear regression model to determine the first cell composition percentage for the first cell type; and outputting the first cell composition percentage.Type: ApplicationFiled: March 29, 2022Publication date: July 21, 2022Applicant: BostonGene CorporationInventors: Aleksandr Zaitsev, Maksim Chelushkin, Ilya Cheremushkin, Ekaterina Nuzhdina, Vladimir Zyrin, Daniiar Dyikanov, Alexander Bagaev, Ravshan Ataullakhanov, Boris Shpak
-
Patent number: 11315658Abstract: Techniques for determining one or more cell composition percentages from expression data. The techniques include obtaining expression data for a biological sample, the biological sample previously obtained from a subject, the expression data including first expression data associated with a first set of genes associated with a first cell type; determining a first cell composition percentage for the first cell type using the expression data and one or more non-linear regression models including a first non-linear regression model, wherein the first cell composition percentage indicates an estimated percentage of cells of the first cell type in the biological sample, wherein determining the first cell composition percentage for the first cell type comprises: processing the first expression data with the first non-linear regression model to determine the first cell composition percentage for the first cell type; and outputting the first cell composition percentage.Type: GrantFiled: March 12, 2021Date of Patent: April 26, 2022Assignee: BostonGene CorporationInventors: Aleksandr Zaitsev, Maksim Chelushkin, Ilya Cheremushkin, Ekaterina Nuzhdina, Vladimir Zyrin, Daniiar Dyikanov, Alexander Bagaev, Ravshan Ataullakhanov, Boris Shpak
-
Publication number: 20210287759Abstract: Techniques for determining one or more cell composition percentages from expression data. The techniques include obtaining expression data for a biological sample, the biological sample previously obtained from a subject, the expression data including first expression data associated with a first set of genes associated with a first cell type; determining a first cell composition percentage for the first cell type using the expression data and one or more non-linear regression models including a first non-linear regression model, wherein the first cell composition percentage indicates an estimated percentage of cells of the first cell type in the biological sample, wherein determining the first cell composition percentage for the first cell type comprises: processing the first expression data with the first non-linear regression model to determine the first cell composition percentage for the first cell type; and outputting the first cell composition percentage.Type: ApplicationFiled: March 12, 2021Publication date: September 16, 2021Inventors: Alexander Zaitsev, Maksim Chelushkin, Ilya Cheremushkin, Ekaterina Nuzhdina, Vladimir Zyrin, Daniyar Dyykanov, Alexander Bagaev, Ravshan Ataullakhanov, Boris Shpak