Machine learning prediction of disrupted 3D genome structure in disease

Aug 2, 2026

A dissertation studying how machine learning can predict disrupted 3D genome structure associated with disease. The work is presented as a peer-reviewed thesis/dissertation from the University of California, San Francisco, detailing supervised research under Dr. Katherine S. Pollard with additional mentorship from Dr. Yin Shen and Dr. Jingjing Li. The document emphasizes computational prediction of genome architecture disruptions and the scientific contributions made across dissertation chapters and authorship.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages123

Reading Time5 h 10 min

AccessFree to download

Acknowledgements

Contributions

Dissertation supervision

Chapter contributions

UCSF UC San Francisco Electronic Theses and Dissertations Title Machine learning prediction of disrupted 3D genome structure in disease Permalink [https://escholarship.org/uc/item/6zp924nd](https://escholarship.org/uc/item/6zp924nd) Author Gjoni, Ketrin Publication Date 2025 Peer reviewed|Thesis/dissertation [eScholarship.org](eScholarship.org) Powered by the California Digital Library University of California 􀀏􀀗􀀘􀀝􀀞"􀀚 􀀚􀀗%"􀀞"􀀜 $%􀀚􀀙􀀞􀀘'􀀞\#" \#􀀛 􀀙􀀞&%($'􀀚􀀙 􀀃􀀆 􀀜􀀚"\#!􀀚 &'%(􀀘'(%􀀚 􀀞" 􀀙􀀞&􀀚􀀗&􀀚 by 􀀍􀀚'%􀀞" 􀀉 \#"􀀞 􀀆􀀋􀀔􀀔􀀇􀀓􀀕􀀄􀀕􀀋􀀑􀀐 Submitted in partial satisfaction of the requirements for degree of 􀀆􀀑􀀅􀀕􀀑􀀓 􀀑􀀈 􀀒􀀊􀀋􀀎􀀑􀀔􀀑􀀒􀀊􀀖 in 􀀒􀀝􀀗%!􀀗􀀘􀀚('􀀞􀀘􀀗 􀀔􀀘􀀞􀀚"􀀘􀀚& 􀀗"􀀙 􀀒􀀝􀀗%!􀀗􀀘\#􀀜􀀚"\#!􀀞􀀘& in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, SAN FRANCISCO Approved: 􀀖􀀞" 􀀔􀀝􀀚" | Chair
􀀍􀀗'􀀝􀀚%􀀞"􀀚 􀀔􀀂 􀀒\# 􀀗%􀀙 | | --- | | 􀀌􀀞"􀀜 􀀞"􀀜 􀀎􀀞 | | | ______________________________________________________________________________ Committee Members ii Dedicated to my family: Lori, Elisabeta, and Maksim Gjoni. ACKNOWLEDGEMENTS My accomplishments are a testament to the support and care from my community. First and foremost, my family and their sacrifices granted me the opportunities that led me here, and their belief in me the courage to pursue them. My mom instilled in me the value of practicality over perfection and my dad’s humor brought a lighthearted perspective, both of which have proven necessary in tackling a PhD. Together, my parents exemplified what I am continuously striving to adopt: working hard and being resilient without sacrificing enjoying life and making memories. My sister, Lori, is my forever guide and source of wisdom. I feel incredibly lucky to have you as both a role model and friend, to hold my hand through the lows and celebrate the highs with. You and Leith provided me with a second home that served as a refuge of uplifting energy when I needed it most. My baby nephew, Khai, reminds me to slow down, smile, and enjoy the present. To my aunts, uncles, and cousins–you are the village that I would not be here without, and I am forever grateful. To my late grandma, Loloi–I will carry your love and silent sacrifices with me forever. Thank you to my whole family for the care, laughter, and love. I feel lucky to have had my partner, Daniel, to lean on throughout this chapter. You were a pillar of support when things got challenging–selflessly showing up for me without hesitation. When I overextended myself and got overwhelmed, you were the calm voice of reason that helped me regain focus and push forward. Your humor and warmth recharged me, while your work ethic and discipline inspired me to stay the course. Thank you for both grounding and uplifting meand reminding me that I was never alone. To the Rowens and Callens, thank you for embracing me and giving me a sense of family in the Bay Area. To my friends–my chosen family–your love, humor, and encouragement were an integral part of this endeavor. From vulnerable conversations to silly bits to fun adventures, you helped me regain perspective and stay grounded. Our friendships taught me to be fully myself, to always have a good time, and to lead with an open mind and heart. Olivia–thank you for your steady stream of love and thoughtfulness and never failing to be a listening ear. Thank you to Alyssa for the positivity, compassion, and adventure. Together, you made our home a safe haven. Carina, Liza, and Maggie–thank you for helping me grow, making me laugh, and giving me a feeling of comfort and belonging. Thank you to Kaela for being my confidant and knowing exactly what to say when I needed it most. Georgia and Claudia along with their families, have shown up for me in big ways and I’ll always be appreciative. Thank you to many more friends who filled my cup with joy in the past 4.5 years: Alex, Charlie, Ellie, Gabe, Jennae, Julie, Noah, Matt, Rachel, Sam, and Suma. Your love and support make a world of a difference. The sense of community from t

FAQs

What is the dissertation topic?

It focuses on using machine learning to predict disrupted 3D genome structure in disease.

Who supervised the dissertation?

The dissertation was supervised by Dr. Katherine S. Pollard, with additional guidance from Dr. Yin Shen and Dr. Jingjing Li.

What do the document’s contributions section describe?

It states where specific contributions appear, including that Chapter 1 contains contributions from listed authors and related work.

Aug 2, 2026

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