Librería Portfolio

Features

One of the first books published on this key topic
Written by a leading practitioner
Focuses on algorithms
Covers technologies used in next-generation sequencing
Includes a wide range of case studies and applications
Solutions manual and figure slides available upon qualifying course adoption

Summary

Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before - as many as hundreds of millions of short reads in the course of a few days. But what are the best ways to deal with this flood of data?

Algorithms for Next-Generation Sequencing is an invaluable tool for students and researchers in bioinformatics and computational biology, biologists seeking to process and manage the data generated by next-generation sequencing, and as a textbook or a self-study resource. In addition to offering an in-depth description of the algorithms for processing sequencing data, it also presents useful case studies describing the applications of this technology.



Table of Contents

Introduction. Reference Alignment. Genome Assembly. Variation Discovery by Mapping to Reference. RNA-seq. ChIP-seq. Meta-Genomic. Other Technologies.