Exploring the Representational Power of Genomic Deep Learning Models

Tang, Ziqi (April 2024) Exploring the Representational Power of Genomic Deep Learning Models. PhD thesis, Cold Spring Harbor Laboratory.

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Item Type: Thesis (PhD)
Subjects: bioinformatics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > cis-regulatory elements
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > epigenetics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > epigenetics
CSHL Authors:
Communities: CSHL labs > Koo Lab
School of Biological Sciences > Theses
Depositing User: Kathleen McGuire
Date: 3 April 2024
Date Deposited: 29 Aug 2024 18:56
Last Modified: 29 Aug 2024 19:08
URI: https://repository.cshl.edu/id/eprint/41644

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