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E-grāmata: Gene Expression Analysis: Methods and Protocols

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  • Formāts: EPUB+DRM
  • Sērija : Methods in Molecular Biology 2880
  • Izdošanas datums: 03-Feb-2025
  • Izdevniecība: Springer-Verlag New York Inc.
  • Valoda: eng
  • ISBN-13: 9781071642764
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Gene Expression Analysis: Methods and ProtocolsPalielināt
  • Formāts: EPUB+DRM
  • Sērija : Methods in Molecular Biology 2880
  • Izdošanas datums: 03-Feb-2025
  • Izdevniecība: Springer-Verlag New York Inc.
  • Valoda: eng
  • ISBN-13: 9781071642764
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This second edition volume expands on the previous edition with updates on the latest methodologies in the transcriptomics field. The chapters in this book cover topics such as spatial omics, long-read sequencing technology, tissue microarrays, analysis of saliva and extracellular vesicles, machine learning and artificial intelligence-based approaches for analysis of singe cells transcriptome, and large sets of data on multi-omics including transcriptomics.  Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.





Cutting-edge and practical, Gene Expression Analysis: Methods and Protocols, Second Edition is a valuable resource for advanced undergraduate and graduate students studying gene expression analysis, and scientists interested in learning more about this rapidly advancing field.
The Salivary Transcriptome: A Window into Local and Systemic Gene
Expression Patterns.- Digital PCR Based Gene Expression Analysis Using a
Highly Multiplexed Assay with Universal Detection Probes to Study Induced
Pluripotent Stem Cell Differentiation into Cranial Neural Crest
Cells.- Identification of Circular RNA Variants by Oxford Nanopore Long-Read
Sequencing.- Combining Short- and Long-Read Transcriptomes for Targeted
Enzyme Discovery.- Spatial-Omics Methods and Applications.- Semi-Quantitative
Cardiac Specific Gene Expression Validation of the DNA Methylation Microarray
in Human Mesenchymal Stem Cells.- Fusion Transcript Detection from Short-Read
RNA-Seq.- RNA-Seq and Gene Set Enrichment Analysis (GSEA) in Peripheral Blood
Mononuclear Cells (PBMCs).- Integrating Tissue Microarray to GeoMx® Digital
Spatial Profiler Spatial Transcriptomics Assay with Bioinformatics
Analysis.- Establishing a De Novo Annotation of Human Liver Transcriptome
Based on Long-Read Direct RNA Sequencing Technology and a Liver-Specific
Humanized Mouse Model.- Exploring Extracellular Vesicle Transcriptomic
Diversity through Long-Read Nanopore Sequencing.- Enhancing Robust and Stable
Feature Selection through the Integration of Ranking Methods and Wrapper
Techniques in Genetic Data Classification.- Accelerating Single-Cell
Sequencing Data Analysis with SciDAP: A User-Friendly Approach.- A Selective
Review of Network Analysis Methods for Gene Expression Data.- Deconvolving
Bulk Transcriptomics Samples to Obtain Cell Type Proportion
Estimates.- Applying AI/ML for Analyzing Gene Expression Patterns.- A Machine
Learning Pipeline to Screen Large In Vivo Molecular Data to Curate Disease
Signatures of High Translational Potential.- Regulatory Perspectives for Gene
Expression-Based Diagnostic Devices.
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