Muutke küpsiste eelistusi

E-raamat: Computational Epigenomics and Epitranscriptomics

  • Formaat: EPUB+DRM
  • Sari: Methods in Molecular Biology 2624
  • Ilmumisaeg: 01-Feb-2023
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9781071629628
  • Formaat - EPUB+DRM
  • Hind: 135,23 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
  • Formaat: EPUB+DRM
  • Sari: Methods in Molecular Biology 2624
  • Ilmumisaeg: 01-Feb-2023
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9781071629628

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

This volume details state-of-the-art computational methods designed to manage, analyze, and generally leverage epigenomic and epitranscriptomic data. Chapters guide readers through fine-mapping and quantification of modifications, visual analytics, imputation methods, supervised analysis, and integrative approaches for single-cell data. 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 thorough, Computational Epigenomics and Epitranscriptomics aims to provide an overview of epiomic protocols, making it easier for researchers to extract impactful biological insight from their data.
DNA methylation data analysis using Msuite.- Interactive DNA methylation
arrays analysis with ShinyÉPICo.- Predicting Chromatin Interactions from DNA
Sequence using DeepC.- Integrating single-cell methylome and transcriptome
data with MAPLE.- Quantitative comparison of multiple chromatin
immunoprecipitation-sequencing (ChIP-seq) experiments with spikChIP.- A Guide
To MethylationToActivity: A Deep-Learning Framework That Reveals Promoter
Activity Landscapes from DNA Methylomes In Individual Tumors.- DNA
modification patterns filtering and analysis using DNAModAnnot.- Methylome
imputation by methylation patterns.- Sequoia: a framework for visual analysis
of RNA modifications from direct RNA sequencing data.- Predicting
pseudouridine sites with Porpoise.- Pseudouridine Identification and
Functional Annotation with PIANO.- Analyzing mRNA epigenetic sequencing data
with TRESS.- Nanopore Direct RNA Sequencing Data Processing and Analysis
Using MasterOfPores.- Data Analysis Pipeline for Detection and Quantification
of Pseudouridine () in RNA by HydraPsiSeq.- Analysis of RNA sequences and
modifications using NASE.- Mapping of RNA modifications by direct Nanopore
sequencing and JACUSA2.