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Bioinformatics with Python Cookbook

You're reading from   Bioinformatics with Python Cookbook Use modern Python libraries and applications to solve real-world computational biology problems

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803236421
Length 360 pages
Edition 3rd Edition
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Author (1):
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Tiago Antao Tiago Antao
Author Profile Icon Tiago Antao
Tiago Antao
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Toc

Table of Contents (15) Chapters Close

Preface 1. Chapter 1: Python and the Surrounding Software Ecology 2. Chapter 2: Getting to Know NumPy, pandas, Arrow, and Matplotlib FREE CHAPTER 3. Chapter 3: Next-Generation Sequencing 4. Chapter 4: Advanced NGS Data Processing 5. Chapter 5: Working with Genomes 6. Chapter 6: Population Genetics 7. Chapter 7: Phylogenetics 8. Chapter 8: Using the Protein Data Bank 9. Chapter 9: Bioinformatics Pipelines 10. Chapter 10: Machine Learning for Bioinformatics 11. Chapter 11: Parallel Processing with Dask and Zarr 12. Chapter 12: Functional Programming for Bioinformatics 13. Index 14. Other Books You May Enjoy

Accessing GenBank and moving around NCBI databases

Although you may have your own data to analyze, you will probably need existing genomic datasets. Here, we will look at how to access such databases from NCBI. We will not only discuss GenBank but also other databases from NCBI. Many people refer (wrongly) to the whole set of NCBI databases as GenBank, but NCBI includes the nucleotide database and many others—for example, PubMed.

As sequencing analysis is a long subject and this book targets intermediate to advanced users, we will not be very exhaustive with a topic that is, at its core, not very complicated.

Nonetheless, it’s a good warm-up for the more complex recipes that we will see at the end of this chapter.

Getting ready

We will use Biopython, which you installed in Chapter 1, Python and the Surrounding Software Ecology. Biopython provides an interface to Entrez, the data retrieval system made available by NCBI.

This recipe is made available in the...

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