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  • 1
    UID:
    almafu_9959234314402883
    Umfang: 1 online resource (xv, 481 pages) : , digital, PDF file(s).
    Ausgabe: 1st ed.
    ISBN: 1-139-89118-9 , 1-107-24941-4 , 1-107-24858-2 , 1-299-70751-3 , 1-107-25107-9 , 1-107-25024-2 , 1-139-22644-4 , 1-107-24775-6
    Inhalt: Providing genome-informed personalized treatment is a goal of modern medicine. Identifying new translational targets in nucleic acid characterizations is an important step toward that goal. The information tsunami produced by such genome-scale investigations is stimulating parallel developments in statistical methodology and inference, analytical frameworks, and computational tools. Within the context of genomic medicine and with a strong focus on cancer research, this book describes the integration of high-throughput bioinformatics data from multiple platforms to inform our understanding of the functional consequences of genomic alterations. This includes rigorous and scalable methods for simultaneously handling diverse data types such as gene expression array, miRNA, copy number, methylation, and next-generation sequencing data. This material is written for statisticians who are interested in modeling and analyzing high-throughput data. Chapters by experts in the field offer a thorough introduction to the biological and technical principles behind multiplatform high-throughput experimentation.
    Anmerkung: Title from publisher's bibliographic system (viewed on 05 Oct 2015). , ""Contents""; ""List of Contributors""; ""Preface""; ""1 An Introduction to Next-Generation Biological Platforms""; ""Virginia Mohlere, Wenting Wang, and Ganiraju Manyam""; ""1.1 Introduction""; ""1.2 The Biology of Gene Silencing""; ""1.2.1 DNA Methylation""; ""1.2.2 RNA Interference""; ""1.3 High-Throughput Profiling""; ""1.3.1 Molecular Inversion Probe Arrays""; ""1.3.2 Array Comparative Genomic Hybridization (aCGH)""; ""1.3.3 Genome-Wide Association Studies""; ""1.3.4 Reverse-Phase Protein Array""; ""1.4 Next-Generation Sequencing""; ""1.4.1 Whole-Genome and Whole-Exome Sequencing"" , ""1.4.2 ChIP-Seq""""1.4.3 RNA-Seq""; ""1.4.4 BS-seq""; ""1.5 NGS Data Management and Analysis""; ""1.6 Platform Integration""; ""Acknowledgments""; ""References""; ""References""; ""2 An Introduction to The Cancer Genome Atlas""; ""Bradley M. Broom and Rehan Akbani""; ""2.1 Introduction""; ""2.2 History and Goals of the TCGA Project""; ""2.3 Sample Collection and Processing""; ""2.3.1 Step 1: Tissue Collection""; ""2.3.2 Step 2: Quality Control and DNA/RNA Extraction""; ""2.3.3 Step 3: Molecular Profiling and Sequencing""; ""2.3.4 Step 4: Data Collection and Public Distribution"" , ""2.3.5 Step 5: Data Analysis""""2.4 Data Processing, Storage, and Access""; ""2.4.1 TCGA Barcodes and UUIDs""; ""2.4.2 The Data Coordinating Center""; ""2.4.3 Data Access Matrix""; ""2.4.4 Bulk Download""; ""2.4.5 HTTP""; ""2.4.6 CGHub""; ""2.4.7 Sample and Data Relationship Format (SDRF) and Investigation Description Format (IDF) Files""; ""2.4.8 File Format""; ""2.4.9 Version""; ""2.5 Tools for Visualizing and Analyzing TCGA Data""; ""2.5.1 cBio Cancer Genomics Portal""; ""2.5.2 MBatch Portal""; ""2.5.3 Next-Generation Clustered Heat Maps""; ""2.5.4 Regulome Explorer"" , ""2.5.5 Integrative Genome Viewer""""2.5.6 Cancer Genomics Browser""; ""2.6 Summary""; ""Acknowledgments""; ""References""; ""References""; ""3 DNA Variant Calling in Targeted Sequencing Data""; ""Wenyi Wang, Yu Fan, and Terence P. Speed""; ""3.1 Introduction""; ""3.2 Background""; ""3.2.1 Single-Nucleotide Variation""; ""3.2.2 Long Padlock Probes""; ""3.2.3 Array-Based Resequencing""; ""3.3 Sequence Robust Multiarray Analysis""; ""3.3.1 Quality Control""; ""3.3.2 Variant Calling""; ""3.4 Application of SRMA""; ""3.4.1 Candidate Gene Study for Mitochondrial Diseases"" , ""3.4.2 Validation Results""""3.4.3 Biological Findings""; ""3.5 Conclusion""; ""Appendix""; ""References""; ""References""; ""4 Statistical Analysis of Mapped Reads from mRNA-Seq Data""; ""Ernest Turro and Alex Lewin""; ""4.1 Background""; ""4.1.1 RNA Biology""; ""4.1.2 RNA Technology""; ""4.2 Mapping and Assembly Strategies""; ""4.2.1 De Novo Assembly of the Transcriptome""; ""4.2.2 Genome-Guided Assembly of the Transcriptome""; ""4.2.3 Alignment to a Reference Transcriptome""; ""4.3 Modeling Expression Levels""; ""4.3.1 Poisson Model for Expression Quantification""; ""4.4 Normalization"" , ""4.4.1 RPKM Normalization"" , English
    Weitere Ausg.: ISBN 1-107-02752-7
    Weitere Ausg.: ISBN 1-107-24154-5
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    UID:
    almahu_9948318392602882
    Umfang: xv, 481 p. : , ill.
    Ausgabe: Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
    Inhalt: "Chapter 1 An introduction to next-generation biological platforms Virginia Mohlere, Wenting Wang, and Ganiraju Manyam The University of Texas. MD Anderson Cancer Center 1.1 Introduction When Sanger and Coulson first described a reliable, efficient method for DNA sequencing in 1975 (Sanger and Coulson, 1975), they made possible the full sequencing of both genes and entire genomes. Although the method was resource-intensive, many institutions invested in the necessary equipment, and Sanger sequencing remained the standard for the next 30 years. Refinement of the process increased read lengths from around 25 to 2 Mohlere, Wang, and Manyam almost 750 base pairs (Schadt et al., 2010, fig. 1). While this greatly increased efficiency and reliability, the Sanger method still required not only large equipment but significant human investment, as the process requires the work of several people. This prompted researchers and companies such as Applied Biosystems to seek improved sequencing techniques and instruments. Starting in the late 2000s, new instruments came on the market that, although they actually decreased read length, lessened run time and could be operated more easily with fewer human resources (Schadt et al., 2010). Despite discoveries that have illuminated new therapeutic targets, clarified the role of specific mutations in clinical response, and yielded new methods for diagnosis and predicting prognosis (Chin et al., 2011), the initial promise of genomic data has largely remained so far unfulfilled. The difficulties are numerous"--
    Sprache: Englisch
    Schlagwort(e): Electronic books.
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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