Sanjit Batra

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2023-58

May 1, 2023

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-58.pdf

The central dogma describes the transformation of DNA into mRNA and consequently into a protein. Any of these three stages could be dysregulated in a disease. In this work, we develop three computational tools aimed at better understanding how diseases such as cancer might affect these different stages. The first method describes an approach to detect and track changes in DNA caused by cancer, such as large-scale structural variants. The second method investigates whether the latest advancements in CRISPR can be leveraged to restore balance to gene regulation that might have been disturbed by disease. Finally, the third method provides a way to detect if mutations affect the abundance of a protein thereby causing disease. Together, these methods span the impact of diseases such as cancer on the central dogma of biology and pave the way for a better understanding of underlying mechanisms and future therapies.

Advisors: Yun S. Song

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BibTeX citation:

@phdthesis{Batra:EECS-2023-58,
    Author= {Batra, Sanjit},
    Title= {Computational methods for regulating transcription and translation},
    School= {EECS Department, University of California, Berkeley},
    Year= {2023},
    Month= {May},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-58.html},
    Number= {UCB/EECS-2023-58},
    Abstract= {The central dogma describes the transformation of DNA into mRNA and consequently into a protein. Any of these three stages could be dysregulated in a disease. In this work, we develop three computational tools aimed at better understanding how diseases such as cancer might affect these different stages. The first method describes an approach to detect and track changes in DNA caused by cancer, such as large-scale structural variants. The second method investigates whether the latest advancements in CRISPR can be leveraged to restore balance to gene regulation that might have been disturbed by disease. Finally, the third method provides a way to detect if mutations affect the abundance of a protein thereby causing disease. Together, these methods span the impact of diseases such as cancer on the central dogma of biology and pave the way for a better understanding of underlying mechanisms and future therapies.},
}

EndNote citation:

%0 Thesis
%A Batra, Sanjit 
%T Computational methods for regulating transcription and translation
%I EECS Department, University of California, Berkeley
%D 2023
%8 May 1
%@ UCB/EECS-2023-58
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-58.html
%F Batra:EECS-2023-58