[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120936-en":3,"doc-seo-120936-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120936,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Methods, Models, and Machine Learning Approaches for Understanding Pathogen-Specific Humoral Immunity - Thesis Abstract","Humoral immune responses rely on extensive polyclonal antibody libraries that recognize diverse targets and regulate innate immune functions. Antibody-profile heterogeneity across populations and diseases complicates identifying the mechanisms that drive protection. Clarifying these mechanisms and their determinants supports defining immunity and guiding vaccine and therapeutic design. This thesis develops experimental and computational methods, including machine learning, to study mechanisms, dynamics, and drivers of pathogen-specific humoral immunity.","Methods, Models, and Machine Learning Approaches for Understanding PathogenSpecific Humoral Immunity  \nby  \nTomer Zohar  \nB.S. Bioengineering  \nUniversity of Maryland, College Park 2017  \nSubmitted to the department of Biological Engineering  \nin partial fulfillment of the requirements for the degree of  \nDoctor of Philosophy in Biological Engineering  \nat the  \nMASSACHUSETTS INSTITUTE OF TECHNOLOGY  \nAugust 2022  \n© 2022 Massachusetts Institute of Technology. All rights reserved  \nSignature of Author………………………………………………………………………………………………………………  \nTomer Zohar  \nDepartment of Biological Engineering August 5, 2022  \nCertified by………………………………………………………………………………………………………………………….  \nDouglas A. Lauffenburger  \nFord Professor of Engineering, MIT Thesis Supervisor  \nCertified by………………………………………………………………………………………………………………………….  \nGalit Alter  \nProfessor of Medicine at Harvard Medical School Thesis Supervisor  \nAccepted by.………………………………………………………………………………………………………………………..  \nKatharina Ribbeck  \nProfessor of Biological Engineering  \nChair of Graduate Program, Department of Biological Engineering  \nThesis Committee Members  \nDarrell J. Irvine, Ph.D. (Chair) Professor, Biological Engineering Massachusetts Institute of Technology  \nDouglas A. Lauffenburger, Ph.D. (Thesis Supervisor) Professor, Biological Engineering  \nMassachusetts Institute of Technology  \nGalit Alter, Ph.D. (Thesis Supervisor) Professor of Medicine  \nHarvard Medical School  \nJacquin C. Niles, M.D., Ph.D.  \nProfessor, Biological Engineering  \nMassachusetts Institute of Technology  \nMethods, Models, and Machine Learning Approaches for Understanding Pathogen-Specific Humoral Immunity  \nby  \nTomer Zohar  \nSubmitted to the Department of Biological Engineering  \non August 5, 2022 in partial fulfillment of the  \nrequirements for the degree of  \nDoctor of Philosophy in Biological Engineering  \nAbstract  \nThe humoral immune response is comprised of vast libraries of polyclonal antibodies capable of recognizing a myriad of targets and directing a spectrum of innate immune functions. The complex heterogeneity in antibody profiles across both populations and diseases makes defining mechanisms of protection difficult. Understanding these mechanisms and the factors that influence them is essential to defining immunity and helps inform the design of vaccines and therapeutics. Thus, in this thesis, I describe five studies that present the development of experimental and computational methods, and machine learning approaches for investigating the mechanisms, dynamics, and determinants of pathogen-specific humoral immunity.  \nThe first study introduces an assay for probing antigen-specific antibody mediated primary monocyte phagocytosis, that is capable of capturing subsequent downstream functions. The second study describes a machine learning approach for defining the correlates of upper and lower respiratory protection against RSV and methods for evaluating vaccine designs. The third study uses machine learning methods to uncover signatures of humoral protection against SARS-CoV-2. The fourth study presents a method for longitudinally modelling humoral immunity that was used to investigate the temporal dynamics of antibody features across individuals with varying COVID-19 severity. Finally, the last study describes a genome-wide association screen of pathogen-specific polyclonal antibody characteristics and functions that was then validated with transcriptomics data. Ultimately, the methods described in this thesis present new approaches for investigating underlying phenomena related to pathogenspecific humoral immunity.  \nThesis Supervisors: Douglas A. Lauffenburger | Galit Alter  \nTitle: Ford Professor of Engineering, MIT | Professor of Medicine at Harvard Medical School  \nContents  \n1 Introduction 10  \n1.1 The immune response against infection and vaccination 10  \n1.2 Polyclonal antibody composition impacts disease Outcome 11  \n1.3 Antibody characteristics and mediated functions 11  \n1.4 Current","cbCaisLzacNUsz6N","https://ap.wps.com/l/cbCaisLzacNUsz6N","pdf",7376954,1,173,"English","en",105,"# Abstract\n## Study 1: Antigen-specific antibody-mediated primary monocyte phagocytosis\n## Study 2: Machine learning correlates of RSV respiratory protection\n## Study 3: Signatures of humoral protection against SARS-CoV-2\n## Study 4: Longitudinal modeling of humoral immunity dynamics\n## Study 5: Genome-wide association of polyclonal antibody characteristics\n# Contents\n## Introduction\n## High-throughput assay for ADMP and downstream functions\n## Correlates of protection against RSV following vaccination\n## SARS-CoV-2 humoral protection signatures","[{\"question\":\"Why is understanding pathogen-specific humoral immunity important for vaccines and therapeutics?\",\"answer\":\"Humoral immunity depends on diverse polyclonal antibody profiles, and the heterogeneity across diseases makes protection mechanisms hard to define. Understanding determinants of protection helps inform vaccine and therapeutic design.\"},{\"question\":\"What experimental capability is introduced in the first study?\",\"answer\":\"The first study presents an assay to probe antigen-specific antibody mediated primary monocyte phagocytosis while capturing downstream functions.\"},{\"question\":\"How does the thesis use machine learning across different pathogens?\",\"answer\":\"It applies machine learning to define correlates of respiratory protection for RSV, to uncover signatures of humoral protection against SARS-CoV-2, and to model longitudinal antibody features linked to COVID-19 severity.\"}]","Methods, Models, and Machine Learning Approaches for Understanding Pathogen-Specific Humoral Immunity - Thesis Abstract | PDF",1785732850,436,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"methods-models-and-machine-learning-approaches-for-understanding-pathogen-specific-humoral-immunity-thesis-abstract","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/methods-models-and-machine-learning-approaches-for-understanding-pathogen-specific-humoral-immunity-thesis-abstract/120936/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is understanding pathogen-specific humoral immunity important for vaccines and therapeutics?","Question",{"text":75,"@type":76},"Humoral immunity depends on diverse polyclonal antibody profiles, and the heterogeneity across diseases makes protection mechanisms hard to define. Understanding determinants of protection helps inform vaccine and therapeutic design.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What experimental capability is introduced in the first study?",{"text":80,"@type":76},"The first study presents an assay to probe antigen-specific antibody mediated primary monocyte phagocytosis while capturing downstream functions.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the thesis use machine learning across different pathogens?",{"text":84,"@type":76},"It applies machine learning to define correlates of respiratory protection for RSV, to uncover signatures of humoral protection against SARS-CoV-2, and to model longitudinal antibody features linked to COVID-19 severity.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]