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Bioinformatics with Python Cookbook Second Edition: Learn how to use modern Python bioinformatics libraries and applications t,Used
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Discover modern, nextgeneration sequencing libraries from Python ecosystem to analyze large amounts of biological dataKey Features: Perform complex bioinformatics analysis using the most important Python libraries and applications Implement nextgeneration sequencing, metagenomics, automating analysis, population genetics, and more Explore various statistical and machine learning techniques for bioinformatics data analysisBook Description:Bioinformatics is an active research field that uses a range of simpletoadvanced computations to extract valuable information from biological data.This book covers nextgeneration 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 realworld 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 webbased pipeline system. This updated edition also includes advanced nextgeneration sequencing filtering techniques. You'll also explore topics such as SNP discovery using statistical approaches under highperformance 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 everincreasing deluge of bioinformatics data.What you will learn: Learn how to process large nextgeneration 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 Highperformance computing techniques with Dask and Spark Visualize protein dataset interactions using Cytoscape Use PCA and Decision Trees, two machine learning techniques, with biological datasetsWho this book is for:This book is for Data data Scientistsscientists, Bioinformatics bioinformatics analysts, researchers, and Python developers who want to address intermediatetoadvanced biological and bioinformatics problems using a recipebased approach. Working knowledge of the Python programming language is expected.
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