UID:
almahu_9949388135802882
Umfang:
1 online resource (379 pages)
ISBN:
9781788019965
,
1788019962
,
9781788019958
,
1788019954
Serie:
Detection science ; 18
Inhalt:
This book will be among the first to cover the detection methods for precision medicine that are set to transform health care in the future.
Anmerkung:
Intro -- Halftitle -- Detection Science Series -- Title -- Copyright -- Preface -- Contents -- Part 1 Biomarkers for Precision Medicine -- Chapter 1 Genome-wide Discovery of MicroRNA Biomarkers for Cancer Precision Medicine -- 1.1 Introduction -- 1.2 A Review of miRNA-based Cancer Biomarkers in Various Clinical Applications -- 1.2.1 Diagnosis -- 1.2.2 Prognosis -- 1.2.3 Prediction of Therapeutic Response -- 1.2.4 Disease Status Monitoring -- 1.3 A Data-driven Methodology for miRNA Biomarker Development -- 1.3.1 Data Collection -- 1.3.2 In Silico Discovery and Validation
,
1.3.3 Clinical Validation -- 1.4 Advantages and Challenges -- Abbreviations -- References -- Chapter 2 Extracellular Vesicles in Precision Medicine -- 2.1 Introduction to Extracellular Vesicles -- 2.1.1 Classification and Biogenesis -- 2.1.2 Composition -- 2.1.3 Isolation and Characterisation -- 2.2 Physiological Roles of EVs -- 2.3 Pathological Roles of EVs -- 2.4 Diagnostic and Monitoring Potential of EVs -- 2.4.1 EV Levels and Size -- 2.4.2 EV DNA -- 2.4.3 EV RNA -- 2.4.4 EV Proteins -- 2.4.5 EV Lipids and Metabolites -- 2.5 Therapeutic Potential of EVs -- 2.6 Conclusions and Future Directions
,
Abbreviations -- References -- Chapter 3 Proteomics in Precision Medicine -- 3.1 Introduction -- 3.2 Sample Preparation for Proteomics -- 3.3 LC-MS Analysis of Digested Peptides -- 3.3.1 LC Separation -- 3.3.2 MS Instrumentation -- 3.3.3 Data Acquisition Modes -- 3.4 Quantitative Proteomics -- 3.4.1 Label-based Quantification -- 3.4.2 Label-free Quantification -- 3.5 Proteomics Data Analysis -- 3.5.1 Peptide Identification -- 3.5.2 Protein Assembly -- 3.5.3 Protein Quantification -- 3.6 Recent Applications of Proteomics in Precision Medicine
,
3.6.1 Proteomics for Biomarker Discovery and Verification -- 3.6.2 Proteomics for Identification of Therapeutic Targets -- 3.6.3 Proteomics for Diagnosis -- Abbreviations -- References -- Chapter 4 Computational Prediction of Tumor Neoantigen for Precision Oncology -- 4.1 Background Introduction -- 4.2 Computation Prediction of Neoantigen from High-throughput Sequencing Data -- 4.2.1 Preparing Input Data: Reference Genome Alignment, Gene-calling and Annotation -- 4.2.2 Isoform Structural Comparison to Visualize Alternative Splicing Events
,
4.2.3 Neoantigen Prediction Based on Peptide Sequence Alignment -- 4.2.4 Neoantigen Binding Affinity by Epitope Prediction Software -- 4.3 PacBio Long-read Sequencing Dataset to Test Computational Tool -- 4.4 Identification of Neoantigen Candidates for Melanoma Immunotherapy Study -- 4.5 Discussion -- References -- Chapter 5 Big Data and Its Emerging Role in Precision Medicine and Therapeutic Response -- 5.1 Introduction -- 5.2 Big Data: Advantages and Milestones -- 5.2.1 Genome -- 5.2.2 Epigenome (Methylome) -- 5.2.3 Transcriptome
,
5.3 Big Data and Its Integration in Therapeutic Response Modeling.
Weitere Ausg.:
Print version: Yang, Mengsu (Michael). Detection Methods in Precision Medicine. Cambridge : Royal Society of Chemistry, ©2020 ISBN 9781788017619
Sprache:
Englisch
Schlagwort(e):
Electronic books.
;
Electronic books.
URL:
https://doi.org/10.1039/9781788019958
