[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120318-en":3,"doc-seo-120318-105":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},120318,1099514067415,"Rowan","https://ap-avatar.wpscdn.com/avatar/100002539d78ffe74a7?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779092875211072502",8,"Research & Report","Discovery of Novel Microglial Homeostasis Modulators Through Machine Learning - Master of Science by Research Thesis","Master of Science by Research thesis detailing a machine-learning driven approach to identify novel microglial homeostasis modulators. The work frames microglia’s roles in healthy and diseased brain states, then maps those biological motivations to an ML-assisted drug discovery workflow. Methods cover dataset sourcing, featurization and cleaning, exploratory chemical diversity analysis, and model tuning and selection via baseline comparisons. The study culminates in a computational screening process supported by lab-driven validation and continuous guidance from collaborators, contributing actionable candidates for further investigation.","This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (e. g. PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following terms and conditions of use:  \n• This work is protected by copyright and other intellectual property rights, which are retained by the thesis author, unless otherwise stated.  \n• A copy can be downloaded for personal non-commercial research or study, without prior permission or charge.  \n• This thesis cannot be reproduced or quoted extensively from without first obtaining permission in writing from the author.  \n• The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the author.  \n• When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given.  \nDiscovery of Novel Microglial Homeostasis Modulators Through Machine Learning  \nAllen Shaw  \nA thesis presented for the degree of Master of Science by Research  \nCentre for Discovery Brain Sciences University of Edinburgh  \nDecember 2024  \nDeclaration  \nI declare that all work presented in this thesis is my own, except where otherwise indicated. This work has not been submitted for any other degree or professional qualification.  \n– Allen Shaw December 12, 2024  \nAcknowledgements  \nI would like to acknowledge Dr. Jing Qiu for proposing this project, Dr. Roderick Carter for conducting the original screening that provided the data for my model, Tom Leah for teaching me all the lab techniques, and Dr. Daga Panas for her constant guidance and support throughout my machine-learning journey, starting from when I knew nothing about ML.  \nTable of Contents  \nABSTRACT..........................................................................................................................................3  \nLAYMAN SUMMARY ............................................................................................................................3  \n1 INTRODUCTION .........................................................................................................................4  \n1.1 PROJECT AIM................................................................................................................................4  \n1.2 MICROGLIA IN HEALTH AND DISEASE ..................................................................................................4  \n1.2.1 Microglia Overview ............................................................................................................... 4  \n1.2.2 Microglia in Health ................................................................................................................ 5  \nMicroglia in Development .............................................................................................................................. 5  \nMicroglia in the Adult Brain ............................................................................................................................ 6  \nRole in immune functions ......................................................................................................................... 6  \nRole in neuroplasticity .............................................................................................................................. 7  \n1.2.3 Microglia in Disease .............................................................................................................. 8  \nNeurodegenerative Diseases ......................................................................................................................... 8  \nAlzheimer’s Disease ................................................................................................................................. 8  \nParkinson’s Disease .................................................................................................................................. 9  \nBeyond Neurodegenerative Dise","cbCaioDMl1zffJSu","https://ap.wps.com/l/cbCaioDMl1zffJSu","pdf",6131578,1,49,"English","en",105,"# Abstract\n# Layman Summary\n# 1 Introduction\n## 1.1 Project Aim\n## 1.2 Microglia in Health and Disease\n## 1.3 ML-Assisted Drug Discovery\n# 2 Methods\n## 2.1 Methods Overview\n## 2.2 Machine Learning\n## 2.2.1 Overview\n## 2.2.2 Data Preparation\n## 2.2.3 Exploratory Data Analysis\n## 2.2.4 Model Tuning and Selection","[{\"question\":\"What biological focus motivates the project in this thesis?\",\"answer\":\"The thesis centers on microglia and their homeostasis, describing microglia in health and in neurodegenerative disease contexts, including Alzheimer’s and Parkinson’s disease.\"},{\"question\":\"What does the ML workflow include before model training?\",\"answer\":\"It includes data preparation steps such as selecting and cleaning the dataset, featurization, and exploratory analysis like chemical diversity assessment.\"},{\"question\":\"How are the machine learning models developed and improved?\",\"answer\":\"Model tuning and selection are performed using baseline models for comparison, followed by selecting tuned approaches to support drug discovery screening.\"}]","Discovery of Novel Microglial Homeostasis Modulators Through Machine Learning - 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