{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/122143"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/122143","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Probing biology on its home turf: Tools for ethology and protein dynamics","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-12-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-12-01","abstract_has_math":false,"creators":["Ravan, Aniket S."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Biophysics & Quant Biology","degree_department":null,"school":null,"contributors":["Gruebele, Martin","Chemla, Yann","Shukla, Diwakar","Nelson, Mark"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-12","date_published":"2023-12","updated_at":"2026-07-22T22:25:00Z","subjects":["Animal Behavior","Protein Dynamics","Computer Vision","Machine Learning","Microscopy"],"languages":["en","eng"],"rights":["Copyright 2023 Aniket Ravan"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/122143","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Gruebele, Martin","Chemla, Yann","Shukla, Diwakar","Nelson, Mark"]},{"key":"dc:creator","label":"Author","values":["Ravan, Aniket S."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-12","2023-12-01"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biophysics & Quant Biology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Animal Behavior","Protein Dynamics","Computer Vision","Machine Learning","Microscopy"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Aniket Ravan"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/122143"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-12-01","The student, Aniket Ravan, accepted the attached license on 2023-11-27 at 13:25.","The student, Aniket Ravan, submitted this Dissertation for approval on 2023-11-27 at 14:08.","This Dissertation was approved for publication on 2023-12-01 at 10:41.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20023 on 2024-03-01 at 13:31:04","Biological systems exist out of equilibrium by constantly exchanging information and energy with their environment. This exchange is characterized by complex interactions at multiple length and time scales. Top-down approaches seeking a mechanistic understanding of biological processes require quantitative observations in the full context of these interactions. This requirement motivates the need to engineer tools that enable probing biological systems closer to their native environment. This work includes efforts in developing two such tools that allow probing the larval zebrafish system in the context of biophysical questions. The thesis is broadly divided into three parts, one part for the introduction, and one part each focusing on one of the techniques. In Chapter 1, I will motivate the need to probe biological systems close to their native environment. Chapter 1 forms the first part of the thesis. Chapter 2-3, I will discuss a novel technique to perform behavioral experiments and pose estimation of larval zebrafish in a 3-D cubic tank. A convolutional neural network model predicts larval poses across various experiments rapidly using a digitally generated and broadly applicable training dataset. In Chapter 4, I will perform objective behavioral analysis of 3-D larval behaviors and compare them with behaviors observed in classical 2-D locomotion assays. The 3-D behavioral analysis reveals the ability of the larva to feint when startled. Chapters 2-4 form the second part of the thesis. In Chapter 5, using the larval zebrafish system, I will broadly describe a technique to perform temperature-dependent FRET measurements of proteins in single cells of live zebrafish on an epifluorescence microscope, allowing observations of protein-protein interactions and changes in protein stability."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Probing biology on its home turf: Tools for ethology and protein dynamics"]}]}],"canonical_facts":{"dc:contributor":["Gruebele, Martin","Chemla, Yann","Shukla, Diwakar","Nelson, Mark"],"dc:creator":["Ravan, Aniket S."],"dc:date":["2023-12","2023-12-01"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-12-01","The student, Aniket Ravan, accepted the attached license on 2023-11-27 at 13:25.","The student, Aniket Ravan, submitted this Dissertation for approval on 2023-11-27 at 14:08.","This Dissertation was approved for publication on 2023-12-01 at 10:41.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20023 on 2024-03-01 at 13:31:04","Biological systems exist out of equilibrium by constantly exchanging information and energy with their environment. This exchange is characterized by complex interactions at multiple length and time scales. Top-down approaches seeking a mechanistic understanding of biological processes require quantitative observations in the full context of these interactions. This requirement motivates the need to engineer tools that enable probing biological systems closer to their native environment. This work includes efforts in developing two such tools that allow probing the larval zebrafish system in the context of biophysical questions. The thesis is broadly divided into three parts, one part for the introduction, and one part each focusing on one of the techniques. In Chapter 1, I will motivate the need to probe biological systems close to their native environment. Chapter 1 forms the first part of the thesis. Chapter 2-3, I will discuss a novel technique to perform behavioral experiments and pose estimation of larval zebrafish in a 3-D cubic tank. A convolutional neural network model predicts larval poses across various experiments rapidly using a digitally generated and broadly applicable training dataset. In Chapter 4, I will perform objective behavioral analysis of 3-D larval behaviors and compare them with behaviors observed in classical 2-D locomotion assays. The 3-D behavioral analysis reveals the ability of the larva to feint when startled. Chapters 2-4 form the second part of the thesis. In Chapter 5, using the larval zebrafish system, I will broadly describe a technique to perform temperature-dependent FRET measurements of proteins in single cells of live zebrafish on an epifluorescence microscope, allowing observations of protein-protein interactions and changes in protein stability."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/122143"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Aniket Ravan"],"dc:subject":["Animal Behavior","Protein Dynamics","Computer Vision","Machine Learning","Microscopy"],"dc:title":["Probing biology on its home turf: Tools for ethology and protein dynamics"],"dc:type":["text"],"thesis:degree_discipline":["Biophysics & Quant Biology"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:00Z"}