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:	Tang, Ziqi
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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