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Can I read Computational Methods for Next Generation Sequencing Data Analysis (Wiley Series in Bioinformatics) on EtoBox?

Computational Methods for Next Generation Sequencing Data Analysis (Wiley Series in Bioinformatics) by Ion Mandoiu, Alexander Zelikovsky (eds.) is a nonfiction available to read on EtoBox.

What is Computational Methods for Next Generation Sequencing Data Analysis (Wiley Series in Bioinformatics) about?

**Introduces readers to core algorithmic techniques for next-generation sequencing (NGS) data analysis and discusses a wide range of computational techniques and applications** This book provides an in-depth survey of some of the recent developments in NGS and discusses mathematical and computational challenges in various application areas of NGS technologies. The 18 chapters featured in this book have been authored by bioinformatics experts and represent the latest work in leading labs actively contributing to the fast-growing field of NGS. The book is divided into four parts: Part I focuses on computing and experimental infrastructure for NGS analysis, including chapters on cloud computing, modular pipelines for metabolic pathway reconstruction, pooling strategies for massive viral sequencing, and high-fidelity sequencing protocols. Part II concentrates on analysis of DNA sequencing data, covering the classic scaffolding problem, detection of genomic variants, including insertions and deletions, and analysis of DNA methylation sequencing data. Part III is devoted to analysis of RNA-seq data. This part discusses algorithms and compares software tools for transcriptome assembly alo

Who reads Computational Methods for Next Generation Sequencing Data Analysis (Wiley Series in Bioinformatics)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Ion Mandoiu, Alexander Zelikovsky (eds.)
Publisher
Wiley & Sons, Incorporated, John
Published
2016
Language
EN
ISBN
9781119272168
Category
nonfiction
Subjects
Computer Science, Engineering, Medical

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