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Stochastic Dynamics and Thermodynamics of Molecular Interactions in the Cell
Stochastic Dynamics and Thermodynamics of Molecular Interactions in the Cell
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202103619
- ISBN
- 9798315761242
- DDC
- 574.191
- 저자명
- Li, Xiangting.
- 서명/저자
- Stochastic Dynamics and Thermodynamics of Molecular Interactions in the Cell
- 발행사항
- [Sl] : University of California, Los Angeles, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 263 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-11, Section: B.
- 주기사항
- Advisor: Chou, Tom.
- 학위논문주기
- Thesis (Ph.D.)--University of California, Los Angeles, 2025.
- 초록/해제
- 요약Cells exploit stochastic and nonequilibrium molecular interactions to achieve high-fidelity control over genetic processes. However, a unified framework linking microscopic kinetics to macroscopic thermodynamics across length and time scales remains lacking. In this dissertation, we develop and apply theoretical and computational tools to probe molecular interactions from single-molecule events up to network-level energy flows. First, for a single nucleosome, we construct Markov models of nucleosome disassembly and characterize firstpassage time distributions for both spontaneous and facilitated pathways. Next, we reduce agent-based models of multimeric RPA-ssDNA binding to low-dimensional stochastic models and ordinary differential equations while preserving essential features of protein-DNA dynamics. We then introduce a stochastic model coupling RNA polymerase and ribosomes to evaluate transcription-translation delay distributions and their impact on gene expression noise. In terms of thermodynamics and information theory, we revisit classical kinetic proofreading in DNA replication and transcription and quantify the trade-offs among sensitivity, speed, and specificity. Finally, by developing martingale theories for Langevin dynamics and Poisson-driven chemical networks, we prove generalized Jarzynski equalities for trajectories halted at stopping times and validate them on proofreading networks. Together, these results deliver analytical predictions and numerical tools that lay the groundwork for understanding the relationships among energy, structure, and function in living cells.
- 일반주제명
- Biophysics
- 일반주제명
- Statistical physics
- 일반주제명
- Physics
- 일반주제명
- Thermodynamics
- 키워드
- Cells exploit
- 기타저자
- University of California, Los Angeles Biomathematics 0121
- 기본자료저록
- Dissertations Abstracts International. 86-11B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798315761242
■035 ▼a(MiAaPQ)AAI32045296
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a574.191
■1001 ▼aLi, Xiangting.
■24510▼aStochastic Dynamics and Thermodynamics of Molecular Interactions in the Cell
■260 ▼a[Sl]▼bUniversity of California, Los Angeles▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a263 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-11, Section: B.
■500 ▼aAdvisor: Chou, Tom.
■5021 ▼aThesis (Ph.D.)--University of California, Los Angeles, 2025.
■520 ▼aCells exploit stochastic and nonequilibrium molecular interactions to achieve high-fidelity control over genetic processes. However, a unified framework linking microscopic kinetics to macroscopic thermodynamics across length and time scales remains lacking. In this dissertation, we develop and apply theoretical and computational tools to probe molecular interactions from single-molecule events up to network-level energy flows. First, for a single nucleosome, we construct Markov models of nucleosome disassembly and characterize firstpassage time distributions for both spontaneous and facilitated pathways. Next, we reduce agent-based models of multimeric RPA-ssDNA binding to low-dimensional stochastic models and ordinary differential equations while preserving essential features of protein-DNA dynamics. We then introduce a stochastic model coupling RNA polymerase and ribosomes to evaluate transcription-translation delay distributions and their impact on gene expression noise. In terms of thermodynamics and information theory, we revisit classical kinetic proofreading in DNA replication and transcription and quantify the trade-offs among sensitivity, speed, and specificity. Finally, by developing martingale theories for Langevin dynamics and Poisson-driven chemical networks, we prove generalized Jarzynski equalities for trajectories halted at stopping times and validate them on proofreading networks. Together, these results deliver analytical predictions and numerical tools that lay the groundwork for understanding the relationships among energy, structure, and function in living cells.
■590 ▼aSchool code: 0031.
■650 4▼aBiophysics
■650 4▼aStatistical physics
■650 4▼aPhysics
■650 4▼aThermodynamics
■653 ▼aStochastic process
■653 ▼aStochastic thermodynamics
■653 ▼aCells exploit
■653 ▼aNonequilibrium molecular
■690 ▼a0786
■690 ▼a0217
■690 ▼a0348
■690 ▼a0605
■71020▼aUniversity of California, Los Angeles▼bBiomathematics 0121.
■7730 ▼tDissertations Abstracts International▼g86-11B.
■790 ▼a0031
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17357932▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
