Discover modern, next-generation sequencing libraries from the
powerful Python ecosystem to perform cutting-edge research and
analyze large amounts of biological data Key Features Perform
complex bioinformatics analysis using the most essential Python
libraries and applications Implement next-generation sequencing,
metagenomics, automating analysis, population genetics, and much
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,
and this book will show you how to manage these tasks using Python.
This updated third edition of the Bioinformatics with Python
Cookbook begins with a quick overview of the various tools and
libraries in the Python ecosystem that will help you convert,
analyze, and visualize biological datasets. Next, you'll cover key
techniques for next-generation sequencing, single-cell analysis,
genomics, metagenomics, population genetics, phylogenetics, and
proteomics with the help of real-world examples. You'll learn how
to work with important pipeline systems, such as Galaxy servers and
Snakemake, and understand the various modules in Python for
functional and asynchronous programming. This book will also help
you explore topics such as SNP discovery using statistical
approaches under high-performance computing frameworks, including
Dask and Spark. In addition to this, you'll explore the application
of machine learning algorithms in bioinformatics. By the end of
this bioinformatics Python book, you'll be equipped with the
knowledge you need to implement the latest programming techniques
and frameworks, empowering you to deal with bioinformatics data on
every scale. What you will learn Become well-versed with data
processing libraries such as NumPy, pandas, arrow, and zarr in the
context of bioinformatic analysis Interact with genomic databases
Solve real-world problems in the fields of population genetics,
phylogenetics, and proteomics Build bioinformatics pipelines using
a Galaxy server and Snakemake Work with functools and itertools for
functional programming Perform parallel processing with Dask on
biological data Explore principal component analysis (PCA)
techniques with scikit-learn Who this book is forThis book is for
bioinformatics analysts, data scientists, computational biologists,
researchers, and Python developers who want to address
intermediate-to-advanced biological and bioinformatics problems.
Working knowledge of the Python programming language is expected.
Basic knowledge of biology will also be helpful.
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