De Aller-Bedste Bøger - over 12 mio. danske og engelske bøger
Levering: 1 - 2 hverdage

Transcriptome Data Analysis

Transcriptome Data Analysisaf Rajeev K Azad
Bag om Transcriptome Data Analysis

This detailed volume presents a comprehensive exploration of the advances in transcriptomics, with a focus on methods and pipelines for transcriptome data analysis. In addition to well-established RNA sequencing (RNA-Seq) data analysis protocols, the chapters also examine specialized pipelines, such as multi-omics data integration and analysis, gene interaction network construction, single-cell trajectory inference, detection of structural variants, application of machine learning, and more. As part of the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that leads to best results in the lab.    Authoritative and practical, Transcriptome Data Analysis serves as an ideal resource for educators and researchers looking to understand new developments in the field, learn usage of the protocols for transcriptome data analysis, and implement the tools or pipelines to address relevant problemsof their interest.   Chapter 4 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Vis mere
  • Sprog:
  • Engelsk
  • ISBN:
  • 9781071638859
  • Indbinding:
  • Hardback
  • Udgivet:
  • 28. juli 2024
  • Størrelse:
  • 178x254x24 mm.
  • Vægt:
  • 921 g.
  • 8-11 hverdage.
  • 21. november 2024
På lager

Normalpris

Abonnementspris

- Rabat på køb af fysiske bøger
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding

Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.

Beskrivelse af Transcriptome Data Analysis

This detailed volume presents a comprehensive exploration of the advances in transcriptomics, with a focus on methods and pipelines for transcriptome data analysis. In addition to well-established RNA sequencing (RNA-Seq) data analysis protocols, the chapters also examine specialized pipelines, such as multi-omics data integration and analysis, gene interaction network construction, single-cell trajectory inference, detection of structural variants, application of machine learning, and more. As part of the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that leads to best results in the lab. 
 
Authoritative and practical, Transcriptome Data Analysis serves as an ideal resource for educators and researchers looking to understand new developments in the field, learn usage of the protocols for transcriptome data analysis, and implement the tools or pipelines to address relevant problemsof their interest.
 
Chapter 4 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Brugerbedømmelser af Transcriptome Data Analysis



Find lignende bøger
Bogen Transcriptome Data Analysis findes i følgende kategorier: