Discover modern, next-generation sequencing libraries from Python ecosystem to analyze large amounts of biological data
Key Features
Perform complex bioinformatics analysis using the most important Python libraries and applications
Implement next-generation sequencing, metagenomics, automating analysis, population genetics, and more
Explore various statistical and machine learning techniques for bioinformatics data analysis
Book DescriptionBioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data.
This book covers next-generation sequencing, genomics, metagenomics, population genetics, phylogenetics, and proteomics. You'll learn modern programming techniques to analyze large amounts of biological data. With the help of real-world examples, you'll convert, analyze, and visualize datasets using various Python tools and libraries.
This book will help you get a better understanding of working with a Galaxy server, which is the most widely used bioinformatics web-based pipeline system. This updated edition also includes advanced next-generation sequencing filtering techniques. You'll also explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks such as Dask and Spark.
By the end of this book, you'll be able to use and implement modern programming techniques and frameworks to deal with the ever-increasing deluge of bioinformatics data.
What you will learn
Learn how to process large next-generation sequencing (NGS) datasets
Work with genomic dataset using the FASTQ, BAM, and VCF formats
Learn to perform sequence comparison and phylogenetic reconstruction
Perform complex analysis with protemics data
Use Python to interact with Galaxy servers
Use High-performance computing techniques with Dask and Spark
Visualize protein dataset interactions using Cytoscape
Use PCA and Decision Trees, two machine learning techniques, with biological datasets
Who this book is forThis book is for Data data Scientistsscientists, Bioinformatics bioinformatics analysts, researchers, and Python developers who want to address intermediate-to-advanced biological and bioinformatics problems using a recipe-based approach. Working knowledge of the Python programming language is expected.
Auflage
Sprache
Verlagsort
Zielgruppe
Editions-Typ
Maße
Höhe: 235 mm
Breite: 191 mm
Dicke: 20 mm
Gewicht
ISBN-13
978-1-78934-469-1 (9781789344691)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Tiago Antao is a bioinformatician currently working in the field of genomics. He was originally a computer scientist performance but he crossed over to computational biology with an MSc in Bioinformatics from the Faculty of Sciences at the University of Porto, Portugal, and a PhD on the spread of drug-resistant malaria from the Liverpool School of Tropical Medicine in the UK. He is one of the co-authors of Biopython, a major bioinformatics package written in Python. In his post-doctoral career, he has worked with human datasets at the University of Cambridge (UK) and with mosquito whole genome sequence data at the University of Oxford (UK). He is currently working as a research scientist at the University of Montana.
Table of Contents
Python and the Surrounding Software Ecology
Next-generation Sequencing
Working with Genomes
Population Genetics
Population Genetics Simulation
Phylogenetics
Using the Protein Data Bank
Bioinformatics pipelines
Python for Big Genomics Datasets
Other Topics in Bioinformatics
Machine learning in Bioinformatics
