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El. knyga: Human Genome Informatics: Translating Genes into Health

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Edited by (Associate Professor, University of New Mexico School of Medicine, USA and Founder and Chairman of Golden Helix Inc.), Edited by (Director, Golden Helix Institute of Biomedical Research, London, UK), Edited by
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Human Genome Informatics: Translating Genes into Health examines the most recent and commonly used electronic tools to translate genomic information into a clinically meaningful format. By analyzing and comparing interpretation methods of whole genome data, the book discusses the possibilities of their application in genomic and translational medicine.

Topics such as electronic decision-making tools, translation algorithms, interpretation and translation of whole genome data for rare diseases and how to rationalize drug use are thoroughly explored. In addition, discussions of current human genome databases and the possibilities of big data in genomic medicine are presented.

With an updated approach on recent techniques and current human genomic databases, the book is a valuable source for students and researchers in genome and medical informatics; it is also ideal for workers in the bioinformatics industry who are interested in recent developments in the field.

  • Provides an overview of the most commonly used electronic tools to translate genomic information into a clinically meaningful format
  • Brings an update on the existing human genomic databases that directly impact genome interpretation
  • Summarizes and comparatively analyses interpretation methods of whole genome data and their application in genomic medicine

Daugiau informacijos

An overview of the most commonly used electronic tools to translate genomic information into a clinically meaningful format
Contributors xiii
Preface xv
Chapter 1 Human Genome Informatics: Coming of Age
1(14)
Christophe G. Lambert
Darrol J. Baker
George P. Patrinos
1.1 Introduction
1(2)
1.2 From Informatics to Bioinformatics and Genome Informatics
3(3)
1.3 Informatics in Genomics Research and Clinical Applications
6(2)
1.3.1 Genome Informatics Analysis
6(1)
1.3.2 Genomics Data Sharing
7(1)
1.3.3 Genomic Variant Reporting and Annotation Tools
8(1)
1.4 Pharmacogenomics and Genome Informatics
8(1)
1.5 Databases, Artificial Intelligence, and Big-Data in Genomics
9(1)
1.6 Conclusions
10(5)
Acknowledgments
10(1)
References
10(5)
PART 1 Human Genome Informatics Applications
Chapter 2 Creating Transparent and Reproducible Pipelines: Best Practices for Tools, Data, and Workflow Management Systems
15(30)
Alexandros Kanterakis
George Potamias
Morris A. Swertz
George P. Patrinos
2.1 Introduction
15(1)
2.2 Existing Workflow Environment
16(2)
2.3 What Software Should Be Part of a Scientific Workflow?
18(3)
2.4 Preparing Data for Automatic Workflow Analysis
21(1)
2.5 Quality Criteria for Modern Workflow Environments
22(8)
2.5.1 Being Able to Embed and to Be Embedded
22(1)
2.5.2 Support Ontologies
23(1)
2.5.3 Support Virtualization
23(1)
2.5.4 Offer Easy Access to Commonly Used Datasets
24(1)
2.5.5 Support and Standardize Data Visualization
25(1)
2.5.6 Enable "Batteries Included" Workflow Environments
26(1)
2.5.7 Facilitate Data Integration, Both for Import and Export
27(1)
2.5.8 Offer Gateways for High Performance Computing Environments
28(1)
2.5.9 Engage Users in Collaborative Experimentation and Scientific Authoring
29(1)
2.6 Benefits From Integrated Workflow Analysis in Bioinformatics
30(3)
2.6.1 Enable Meta-Studies, Combine Datasets, and Increase Statistical Power
30(1)
2.6.2 Include Methods and Data From Other Research Disciplines
30(1)
2.6.3 Fight the Reproducibility Crisis
31(1)
2.6.4 Spread of Open Source Policies in Genetics and Privacy Protection
31(1)
2.6.5 Help Clinical Genetics Research
32(1)
2.7 Discussion
33(12)
References
33(12)
Chapter 3 How Cytogenetics Paradigms Shape Decision Making in Translational Genomics
45(16)
Christophe G. Lambert
3.1 Introduction
45(1)
3.2 Clinical Cytogenetic Testing
45(11)
3.2.1 Karyotyping
45(2)
3.2.2 Chromosomal Microarrays
47(9)
3.3 From Cytogenetics to Cytogenomics in the Era of Next-Generation Sequencing
56(1)
3.4 Conclusions
57(4)
References
58(3)
Chapter 4 An Introduction to Tools, Databases, and Practical Guidelines for NGS Data Analysis
61(30)
Alexandras Kanterakis
George Potamias
George P. Patrinos
4.1 Introduction
61(1)
4.2 Data Formats
62(2)
4.3 Data Sources
64(2)
4.4 Variant Data
66(1)
4.5 NGS Pipelines
67(11)
4.5.1 Read Alignment
67(2)
4.5.2 Variant Calling
69(2)
4.5.3 Downstream Analysis
71(1)
4.5.4 RNA-seq
72(5)
4.5.5 ChIP-Seq
77(1)
4.6 Discussion
78(13)
References
80(11)
Chapter 5 Proteomics and Metabolomics Data Analysis for Translational Medicine
91(18)
Theodora Katsila
George P. Patrinos
5.1 Introduction
91(1)
5.2 The Need to Bridge the Gaps in the Era of Precision Medicine
92(1)
5.3 Clinical Proteomics
93(4)
5.3.1 The Power of the Proteome
93(3)
5.3.2 Steps Prior to Routine Proteome Analyses
96(1)
5.4 Clinical Metabolomics
97(1)
5.4.1 The Advances and Promises of Metabolome
97(1)
5.4.2 Needs Prior to Routine Metabolome Analyses
98(1)
5.5 Computational and Chemoinformatic Tools
98(1)
5.6 Strategies to Address Data Complexity
99(2)
5.7 From Translational Medicine Data to Theranostics
101(2)
5.8 Conclusions
103(6)
Acknowledgments
103(1)
References
103(6)
Chapter 6 Incentives for Human Genome Variation Data Sharing
109(24)
George P. Patrinos
6.1 Introduction
109(1)
6.2 Database Projects Linked to Scientific Journals
110(2)
6.3 Microattribution and Nanopublication: An Innovative Publication Modality
112(7)
6.3.1 The Concept of Microattribution
113(3)
6.3.2 The Microattribution Process
116(1)
6.3.3 Implementation of Microattribution
117(2)
6.4 Microattribution: Hurdles From Concept to Implementation
119(3)
6.5 Proposed Measures and Steps Forward
122(3)
6.6 Conclusions
125(8)
References
127(6)
PART 2 Human Genome Informatics Tools and Related Resources
Chapter 7 A Review of Tools to Automatically Infer Chromosomal Positions From dbSNP and HGVS Genetic Variants
133(24)
Alexandras Kanterakis
Theodora Katsila
George Potamias
George P. Patrinos
Morris A. Swertz
7.1 Introduction
133(4)
7.2 Existing Tools for HGVS Position Resolution
137(8)
7.2.1 Mutalyzer
137(1)
7.2.2 The HGVS Python Package
138(1)
7.2.3 Variant Effect Predictor
139(1)
7.2.4 Variation Reporter
140(2)
7.2.5 Transvar
142(1)
7.2.6 BioPython
143(2)
7.3 The MutationInfo Pipeline
145(3)
7.4 Results
148(4)
7.4.1 Analysis of dbSNP Variants
149(2)
7.4.2 Analysis of HGVS Variants
151(1)
7.5 Discussion
152(1)
7.6 Conclusions
152(5)
References
154(3)
Chapter 8 Translating Genomic Information to Rationalize Drug Use
157(22)
Alexandras Kanterakis
Theodora Katsila
George P. Patrinos
8.1 Introduction
157(2)
8.2 Personalized PGx Profiling Using Whole Genome Sequencing
159(2)
8.3 Towards Pharmacogenomic Data Integration
161(5)
8.3.1 The Concept of Integrated PGx Assistant Services
162(1)
8.3.2 Development of an Electronic PGx Assistant
163(3)
8.4 Personalized PGx Translation Services
166(2)
8.5 The Electronic PGx Assistant
168(5)
8.5.1 Explore Service
169(2)
8.5.2 Translation Service
171(1)
8.5.3 Update Services
171(2)
8.6 Translating PGx Knowledge Into Clinical Decision-Making
173(2)
8.7 Conclusion and Future Perspectives
175(4)
Acknowledgments
176(1)
References
176(3)
Chapter 9 Minimum Information Required for Pharmacogenomics Experiments
179(16)
J. Kumuthini
L. Zass
Emilson Chimusa
Melek Chaouch
Collen Masimiremwa
9.1 Pharmacogenomics
179(1)
9.2 Data Standardization
180(2)
9.3 Minimum Information Required for a DMET Experiment
182(7)
9.3.1 Background
182(1)
9.3.2 DMET Console Software Analysis
183(1)
9.3.3 MIDE
184(1)
9.3.4 Discussion
185(4)
9.4 Pharmacogenomics Standardization: Challenges
189(1)
9.5 Conclusions
190(5)
References
191(2)
Further Reading
193(2)
Chapter 10 Human Genomic Databases in Translational Medicine
195(28)
Theodora Katsila
Emmanouil Viennas
Marina Bartsakoulia
Aggeliki Komianou
Konstantinos Sarris
Giannis Tzimas
George P. Patrinos
10.1 Introduction
195(1)
10.2 Historical Overview of Genomic Databases
196(1)
10.3 Genomic Database Types
196(3)
10.4 Models for Database Management
199(1)
10.5 General Variation Databases: Documentation of Variants of Clinical Significance
200(3)
10.5.1 ClinVar Database
200(3)
10.5.2 Data Sharing in ClinVar
203(1)
10.6 Locus-Specific Databases in Translational Medicine
203(5)
10.6.1 Comparison Among Various LSDBs
203(1)
10.6.2 Identification of Causative Genomic Variants
204(1)
10.6.3 Linking Genotype Information With Phenotypic Patterns
205(2)
10.6.4 Selection of the Optimal Variant Allele Detection Strategy
207(1)
10.7 National/Ethnic Genomic Databases: Archiving the Genomic Basis of Human Disorders on a Population-Specific Basis
208(4)
10.8 NEGDBs in a Molecular Diagnostics Setting
212(2)
10.8.1 NEGDBs and Society
213(1)
10.9 Database Management Systems for LSDBs and NEGDBs
214(2)
10.10 Future Challenges
216(2)
10.11 Conclusions
218(5)
Acknowledgments
218(1)
References
218(5)
Chapter 11 Artificial Intelligence: The Future Landscape of Genomic Medical Diagnosis: Dataset, In Silico Artificial Intelligent Clinical Information, and Machine Learning Systems
223(46)
Darrol J. Baker
11.1 Introduction
223(1)
11.2 What Is Artificial Intelligence and Machine Learning?
224(1)
11.2.1 Clinical Genomics Medical AI
224(1)
11.2.2 The Emerging Role of AI
225(1)
11.3 Artificial Intelligence: The Al, The Whole AI, and Nothing but the AI
225(23)
11.3.1 Building an Artificial Intelligence Framework (AIF)
226(3)
11.3.2 Security and Quantum Computing (QComp)
229(1)
11.3.3 Complex Knowledge Management Systems I
230(6)
11.3.4 Epochs Intelligence for Clinical Diagnostics Understanding
236(4)
11.3.5 Clinical Patient Understanding
240(1)
11.3.6 Epoch Deep Belief Neural Networks
241(3)
11.3.7 Educational Aside
244(1)
11.3.8 Extracting Information From the Medical Record
245(1)
11.3.9 Eliciting Information From Experts
246(2)
11.3.10 The Next Steps in Clinical Al
248(1)
11.4 Connecting Artificial Intelligence and Machine Learning Metadata Analysis for Clinical Diagnostic Discovery
248(13)
11.5 Conclusions
261(8)
Acknowledgments
262(1)
References
262(5)
Further Reading
267(2)
Chapter 12 Genomics England: The Future of Genomic Medical Diagnosis: Governmental Scale Clinical Sequencing and Potential Walled-Garden Impact on Global Data Sharing
269(24)
Darrol J. Baker
12.1 Introduction
269(2)
12.2 Understanding the Genomics England Approach to Clinical Genomic Discovery
271(19)
12.3 Conclusions
290(3)
Acknowledgments
290(1)
References
290(2)
Further Reading
292(1)
Index 293
Dr. Christophe G. Lamberts research interests span bioinformatics, cheminformatics and clinical research informatics. He has spent his career developing informatics solutions for biomedical research that has been used by thousands of scientists. Darrol Bakers research interests focus on bioinformatics, particularly in making lifestyle decisions based on genomic information. George P. Patrinos is a Professor of Pharmacogenomics and Pharmaceutical Biotechnology in the University of Patras (Greece), Department of Pharmacy, and Head of Division of Pharmacology and Biosciences of the same department and holds adjunct Full Professorships at Erasmus MC, Faculty of Medicine, and Health Sciences, Rotterdam (the Netherlands), and the United Arab Emirates University, College of Medicine, Department of Genetics and Genomics, Al-Ain (UAE). Also, from 2018 until the end of 2024, he was Chair of the Global Genomic Medicine Collaborative (G2MC). He served 12.5 years as a full member and Greeces National representative in the CHMP Pharmacogenomics Working Party of the European Medicines Agency (EMA). George has more than 340 publications in peer-reviewed scientific journals, some of them in leading scientific journals, such as The Lancet, Nature Genetics, Nature Reviews Genetic, Nucleic Acids Research, Genes & Development. He has also coauthored and coedited more than 15 textbooks, among which the renowned textbook Molecular Diagnostics, published by Academic Press, now in its 3rd edition, while he is the editor of Translational and Applied Genomics book series, published by Elsevier. Furthermore, he serves as the Editor-In-Chief of the prestigious Pharmacogenomics Journal (TPJ), published by Nature Publishing Group, Associate Editor, and member of the editorial board of several scientific journals, and advisory and evaluation committees. Apart from that, George is the main coorganizer of the Golden Helix Conferences, an international meeting series on Pharmacogenomics and Genomic Medicine with more than 50 conferences organized in more than 25 countries worldwide.
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