{"id":{"repo_id":"washington","oai_identifier":"oai:digital.lib.washington.edu:1773/42182"},"canonical_url":"https://search.dev.ndltd.org/etd/washington/oai:digital.lib.washington.edu:1773/42182","repository":{"repo_id":"washington","name":"University of Washington","base_url":"https://digital.lib.washington.edu/server/oai/request"},"display":{"title":"Some Problems in Stochastic Dynamics and Statistical Analysis of Single-Cell Biology of Cancer","abstract":"With the development of experimental apparatus and data processing softwares, one now has easy access to cancer related data on a single cell, its genome and/or molecular compositions. At this level of description, stochasticity is a significant component of the dynamics. Statistics also emerge naturally from stochastic data. In the first part, we study the cancer cell growth data with statistics, and build stochastic models to show that there exists multiple phenotypes in seemingly homogeneous cells. In the second part, we use branching processes to explain the phenomenon that the proportions of different phenotypes of cancer cells will always converge. In the third part, we consider how to quantify the causal effect from a random variable to a response variable. We prove that in special cases quantifying causal effect is impossible. In the fourth part, we consider the lifting of stochastic processes, and prove the convergence of related thermodynamic quantities, so as to explain the origin of entropy production.","abstract_html":"With the development of experimental apparatus and data processing softwares, one now has easy access to cancer related data on a single cell, its genome and/or molecular compositions. At this level of description, stochasticity is a significant component of the dynamics. Statistics also emerge naturally from stochastic data. In the first part, we study the cancer cell growth data with statistics, and build stochastic models to show that there exists multiple phenotypes in seemingly homogeneous cells. In the second part, we use branching processes to explain the phenomenon that the proportions of different phenotypes of cancer cells will always converge. In the third part, we consider how to quantify the causal effect from a random variable to a response variable. We prove that in special cases quantifying causal effect is impossible. In the fourth part, we consider the lifting of stochastic processes, and prove the convergence of related thermodynamic quantities, so as to explain the origin of entropy production.","abstract_has_math":false,"creators":["Wang, Yue"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Qian, Hong"],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-07-31","date_published":"2018-07-31","updated_at":"2026-07-24T05:58:23Z","subjects":["Cancer biology","Causal inference","Entropy productions","Population dynamics","Stochastic processes","Applied mathematics","Biology","Statistics"],"languages":["en_US"],"rights":["CC BY-NC-ND"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1773/42182","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Qian, Hong"]},{"key":"dc:creator","label":"Author","values":["Wang, Yue"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2018-07-31T21:08:56Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2018-07-31T21:08:56Z"]},{"key":"dc:date.issued","label":"Date","values":["2018-07-31"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Cancer biology","Causal inference","Entropy productions","Population dynamics","Stochastic processes","Applied mathematics","Biology","Statistics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]},{"key":"dc:rights","label":"Dc Rights","values":["CC BY-NC-ND"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["Wang_washington_0250E_18616.pdf"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1773/42182"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (Ph.D.)--University of Washington, 2018"]},{"key":"dc:description.abstract","label":"Abstract","values":["With the development of experimental apparatus and data processing softwares, one now has easy access to cancer related data on a single cell, its genome and/or molecular compositions. At this level of description, stochasticity is a significant component of the dynamics. Statistics also emerge naturally from stochastic data. In the first part, we study the cancer cell growth data with statistics, and build stochastic models to show that there exists multiple phenotypes in seemingly homogeneous cells. In the second part, we use branching processes to explain the phenomenon that the proportions of different phenotypes of cancer cells will always converge. In the third part, we consider how to quantify the causal effect from a random variable to a response variable. We prove that in special cases quantifying causal effect is impossible. In the fourth part, we consider the lifting of stochastic processes, and prove the convergence of related thermodynamic quantities, so as to explain the origin of entropy production."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Some Problems in Stochastic Dynamics and Statistical Analysis of Single-Cell Biology of Cancer"]}]}],"canonical_facts":{"dc:contributor.advisor":["Qian, Hong"],"dc:creator":["Wang, Yue"],"dc:date.accessioned":["2018-07-31T21:08:56Z"],"dc:date.available":["2018-07-31T21:08:56Z"],"dc:date.issued":["2018-07-31"],"dc:description":["Thesis (Ph.D.)--University of Washington, 2018"],"dc:description.abstract":["With the development of experimental apparatus and data processing softwares, one now has easy access to cancer related data on a single cell, its genome and/or molecular compositions. At this level of description, stochasticity is a significant component of the dynamics. Statistics also emerge naturally from stochastic data. In the first part, we study the cancer cell growth data with statistics, and build stochastic models to show that there exists multiple phenotypes in seemingly homogeneous cells. In the second part, we use branching processes to explain the phenomenon that the proportions of different phenotypes of cancer cells will always converge. In the third part, we consider how to quantify the causal effect from a random variable to a response variable. We prove that in special cases quantifying causal effect is impossible. In the fourth part, we consider the lifting of stochastic processes, and prove the convergence of related thermodynamic quantities, so as to explain the origin of entropy production."],"dc:format.mimetype":["application/pdf"],"dc:identifier.other":["Wang_washington_0250E_18616.pdf"],"dc:identifier.uri":["http://hdl.handle.net/1773/42182"],"dc:language.iso":["en_US"],"dc:rights":["CC BY-NC-ND"],"dc:subject":["Cancer biology","Causal inference","Entropy productions","Population dynamics","Stochastic processes","Applied mathematics","Biology","Statistics"],"dc:title":["Some Problems in Stochastic Dynamics and Statistical Analysis of Single-Cell Biology of Cancer"],"dc:type":["Thesis"]},"updated_at":"2026-07-24T05:58:23Z"}