Cancer Bioinformatics (häftad)
Fler böcker inom
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
280
Utgivningsdatum
2019-12-10
Upplaga
Softcover reprint of the original 1st ed. 2019
Förlag
Humana Press Inc.
Medarbetare
Krasnitz, Alexander (ed.)
Illustrationer
64 Illustrations, color; 25 Illustrations, black and white; X, 280 p. 89 illus., 64 illus. in color.
Dimensioner
254 x 178 x 178 mm
Vikt
559 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9781493994045

Cancer Bioinformatics

Häftad,  Engelska, 2019-12-10
1246
Billigast på PriceRunner
  • Skickas från oss inom 7-10 vardagar.
  • Fri frakt över 249 kr för privatkunder i Sverige.
Finns även som
Visa alla 2 format & utgåvor
This volume covers a wide variety of state of the art cancer-related methods and tools for data analysis and interpretation. Chapters were designed to attract a broad readership, ranging from active researchers in computational biology and bioinformatics developers, clinical oncologists, and anti-cancer drug developers wishing to rationalize their search for new compounds. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, installation instructions for computational tools discussed, explanations of the input and output formats, and illustrative examples of applications. Authoritative and cutting-edge, Cancer Bioinformatics: Methods and Protocols aims to support researchers performing computational analysis of cancer-related data.
Visa hela texten

Passar bra ihop

  1. Cancer Bioinformatics
  2. +
  3. Can't Hurt Me

De som köpt den här boken har ofta också köpt Can't Hurt Me av David Goggins (häftad).

Köp båda 2 för 1541 kr

Kundrecensioner

Har du läst boken? Sätt ditt betyg »

Innehållsförteckning

An Access Primer to Repositories of Cancer-related Genomic Big Data.- Building Portable and Reproducible Cancer Informatics Workflows: An RNA Sequencing Case Study.- Computational Analysis of Structural Variation in Cancer Genomes.- CORE: A Software Tool for Delineating Regions of Recurrent DNA Copy Number Alteration in Cancer.- Identification of Mutated Cancer Driver Genes on Unpaired RNA-Seq Samples.- A Computational Protocol for Detecting Somatic Mutations by Integrating DNA and RNA Sequencing.- Allele-specific Expression Analysis in Cancer Using Next Generation Sequencing Data.- Computational Analysis of lncRNA Function in Cancer.- Computational Methods for Identification of T Cell Neoepitopes in Tumors.- Computational and Statistical Analysis of Array-based DNA Methylation Data.- Computational Methods for Subtyping Of Tumors and their Applications for Deciphering Tumor Heterogeneity.- Statistically Supported Identification of Tumor Subtypes.- Computational Methods for Analysisof Tumor Clonality and Evolutionary History.- Predictive Modeling of Anti-cancer Drug Sensitivity from Genetic Characterizations.- In silico Oncology Drug Repositioning and Polypharmacology.- Modelling Growth of Tumours and their Spreading Behaviour using Mathematical Functions.