Bioinformatics with Python Cookbook - Second Edition | Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology

Editor

Packt Publishing

Fecha de publicaci�n

2018

Idioma

Ingl�s

ISBN 10

1789344697

ISBN 13

9781789344691

Encuadernaci�n

Taschenbuch

Edici�n

2� Edici�n

Estado

Neu

Dimensiones

Peso

672 gramos

Cat�logos de vendedores

B�cher

Acerca de

Sinopsis

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 Description:

Bioinformatics 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 for:

This 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.

Acerca del autor

Tiago Antao is a bioinformatician currently working in the field of genomics. A former computer scientist, Tiago moved into 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 (UK). Postdoctoral, Tiago has worked with human datasets at the University of Cambridge (UK) and with mosquito whole genome sequencing data at the University of Oxford (UK), before helping to set up the bioinformatics infrastructure at the University of Montana. He currently works as a data engineer in the biotechnology field in Boston, MA. He is one of the co-authors of Biopython, a major bioinformatics package written in Python.

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