Xinkun Wang

Next-Generation Sequencing Data Analysis (eBook, PDF)

• Format: PDF

Produktbeschreibung

Next-Generation Sequencing Data Analysis walks readers through NGS data analysis step-by-step for a wide range of NGS applications.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 434
• Erscheinungstermin: 6. Juli 2023
• Englisch
• ISBN-13: 9781000897197
• Artikelnr.: 68109390

Autorenporträt

Dr. Xinkun Wang is a research professor and the director of the Next-Generation Sequencing Facility at Northwestern University in Chicago. Dr. Wang's first foray into the genomics field was during his doctoral training, performing microarray-based gene expression analysis. From 2005 to 2015, he was the founding director of the University of Kansas Genomics Facility, prior to moving to Northwestern to head the Northwestern University Sequencing Facility (NUSeq) in late 2015. Dr. Wang is a renowned expert on genomics technologies and data mining, and their applications to the biomedical field. Besides his monographic publications, he has published extensively in neuroscience, with a focus on brain aging and neurodegenerative diseases (mostly Alzheimer's disease).

Dr. Wang has served as principal investigator on dozens of grants. Dr. Wang's other professional activities include serving on journal editorial boards, and as reviewers for journals, publishers, and funding agencies. Dr. Wang is a member of American Society of Human Genetics, Association of Biomolecular Resource Facilities, the Honor Society of Phi Kappa Phi, and Society for Neuroscience. Dr. Wang was born in Shandong province, China, and is a first-generation college graduate. His off-work hobbies include cycling and Alpine skiing.

Inhaltsangabe

1. The Cellular System and The Code of Life. 2. DNA Sequence: the Genome
Base. 3. RNA: the Transcribed Sequence. 4. Next-Generation Sequencing (NGS)
Technologies: Ins and Outs. 5. Early-Stage Next-Generation Sequencing (NGS)
Data Analysis: Common Steps. 6. Computing Needs for Next-Generation
Sequencing (NGS) Data Management and Analysis. 7. Transcriptomics by Bulk
RNA-Seq. 8. Transcriptomics by Single Cell RNA-Seq. 9. Small RNA
Sequencing. 10. Genotyping and Variation Discovery by Whole Genome/Exome
Sequencing. 11. Clinical Sequencing and Detection of Actionable Variants.
12. De Novo Genome Assembly with Long and/or Short Reads. 13. Mapping
Protein-DNA Interactions with ChIP-Seq. 14. Epigenomics by DNA Methylation
Sequencing. 15. Whole Metagenome Sequencing for Microbial Community
Analysis. 16. What's Next for Next-Generation Sequencing (NGS)?.