Invention Grant
- Patent Title: Denoising ATAC-seq data with deep learning
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Application No.: US16236797Application Date: 2018-12-31
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Publication No.: US11657897B2Publication Date: 2023-05-23
- Inventor: Johnny Israeli , Nikolai Yakovenko
- Applicant: NVIDIA Corporation
- Applicant Address: US CA Santa Clara
- Assignee: NVIDIA Corporation
- Current Assignee: NVIDIA Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: Fisherbroyles LLP
- Agent Adam Whiting
- Main IPC: C12Q1/68
- IPC: C12Q1/68 ; G06N3/08 ; G16B20/30 ; G16B40/00 ; G16B30/00 ; G16B25/00 ; G16B5/20 ; C12Q1/6869 ; G16B25/10 ; G16B40/10

Abstract:
The present invention provides methods, systems, computer program products that use deep learning with neural networks to denoise ATAC-seq datasets. The methods, systems, and programs provide for increased efficiency, accuracy, and speed in identifying genomic sites of chromatin accessibility in a wide range of tissue and cell types.
Public/Granted literature
- US20200211674A1 Denoising ATAC-Seq Data With Deep Learning Public/Granted day:2020-07-02
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