[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124671-en":3,"doc-seo-124671-105":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},124671,962075006959,"Anda","https://ap-avatar.wpscdn.com/avatar/e0002397efbe92a78e?_k=1776741047341049297",8,"Research & Report","Applications of bioinformatics and machine learning in the analysis of proteomics data","This thesis investigates how bioinformatics and machine learning can improve the analysis of proteomics data. It addresses key challenges across proteomics and phosphoproteomics profiling, including profiling in drug-adapted melanoma models and examining PD-1-related mechanisms in CD8+ T cell activation using proteomic and phosphoproteomic measurements. The work also develops a deep learning strategy to identify protein complexes by integrating protein abundance with interaction stoichiometries. The study provides a comprehensive framework and future directions for data-driven proteomics analysis.","Applications of bioinformatics and machine learning in the analysis of proteomics data  \nBohui Li 李伯会  \nISBN: 978-94-6469-375-1  \nThe research in this thesis was performed in the Biomolecular Mass Spectrometry and Proteomics Group, Utrecht University, Utrecht, The Netherlands  \nApplications of bioinformatics and machine learning in the analysis of proteomics data  \nToepassingen van bioinformatica en machine  \nlearning bij de analyse van proteomics data (met een samenvatting in het Nederlands)  \nProefschrift  \nter verkrijging van de graad van doctor aan de  \nUniversiteit Utrecht  \nop gezag van de  \nrector magnificus, prof.dr. H. R. B. M. Kummeling, ingevolge het besluit van het college voor promoties in het openbaar te verdedigen op  \nmaandag 26 juni 2023 des middags te 2.15 uur  \ndoor  \nBohui Li  \ngeboren op 9 november 1986  \nte Guizhou, China  \nPromotor:  \nProf. dr. A. F. M. Altelaar Copromotor:  \n[Dr. ir. B. van](Dr. ir. B. van) Breukelen  \nContents  \nChapter 1  \nGeneral Introduction 7  \nChapter 2  \nProteomics and Phosphoproteomics Profiling of Drug-Addicted  \nBRAFi-Resistant Melanoma Cells 45  \nChapter 3  \nExploring the role of PD-1 in CD8+ T cell activation by Proteomicand phosphoproteomics profiling 73  \nChapter 4  \nIdentification of protein complexes by integrating protein abundance and interaction stoichiometries using a deep learning strategy 101  \nChapter 5  \nSummary and future outlook 133  \nChapter 1  \nGeneral Introduction  \n1 General introduction  \n1.1 Proteomics: from genetic information to cellular function  \nThe rapid development of high-throughput technologies has contributed to our understanding of the cell biology and complex diseases from a perspective of the molecular level. Three types of biomolecules, i.e. , DNA, RNA, and proteins, are indispensable components in understanding cell activity and signaling (1) . In the past decades, efforts have been made to build whole-genome-sequencing databases for numerous organisms, including human (2, 3), or to seek traits-associated genetic variations, such as disease-associated single-nucleotide polymorphisms (SNPs) (4, 5) . The study of the whole genome within an organism is termed genomics (Figure 1) and is focused on DNA molecules. On the other hand, transcriptomics (Figure 1), is seeking to study the total RNA transcripts in the cells or tissues. Transcriptomics has become increasingly popular (6) . Because gene transcription and subsequent RNA translation give rise to functional proteins, studying DNA and RNA expression would be expected to provide a good estimate for protein regulation. However, an increasing number of reports on mRNA and protein abundances find only a weak correlation between the respective abundances of RNA and proteins (7) .  \nFigure 1. Biochemical context of genomics, transcriptomics, and proteomics.","cbCaiqZpVjtbt6FG","https://ap.wps.com/l/cbCaiqZpVjtbt6FG","pdf",23420495,1,154,"English","en",105,"# Contents\n## Chapter 1 General Introduction\n## Chapter 2 Proteomics and Phosphoproteomics Profiling of Drug-Addicted BRAFi-Resistant Melanoma Cells\n## Chapter 3 Exploring the role of PD-1 in CD8+ T cell activation by Proteomic and phosphoproteomics profiling\n## Chapter 4 Identification of protein complexes by integrating protein abundance and interaction stoichiometries using a deep learning strategy\n## Chapter 5 Summary and future outlook","[{\"question\":\"What is the focus of this thesis?\",\"answer\":\"The thesis focuses on applying bioinformatics and machine learning to analyze proteomics data, including proteomic and phosphoproteomic profiling and complex identification.\"},{\"question\":\"Which biological systems and questions are studied?\",\"answer\":\"It studies drug-addicted BRAFi-resistant melanoma cells using proteomics/phosphoproteomics profiling and explores the role of PD-1 in CD8+ T cell activation.\"},{\"question\":\"How does the thesis approach protein complex identification?\",\"answer\":\"It presents a deep learning strategy that integrates protein abundance with interaction stoichiometries to identify protein complexes.\"}]","Applications of bioinformatics and machine learning in the analysis of proteomics data | 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is the focus of this thesis?","Question",{"text":75,"@type":76},"The thesis focuses on applying bioinformatics and machine learning to analyze proteomics data, including proteomic and phosphoproteomic profiling and complex identification.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which biological systems and questions are studied?",{"text":80,"@type":76},"It studies drug-addicted BRAFi-resistant melanoma cells using proteomics/phosphoproteomics profiling and explores the role of PD-1 in CD8+ T cell activation.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the thesis approach protein complex identification?",{"text":84,"@type":76},"It presents a deep learning strategy that integrates protein abundance with interaction stoichiometries to identify protein 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