Deliver to 
Free Shipping
  • Served Customers
  • Secure Payments
  • Served Customers
24/7 Live Chat
Mastering Python For Bioinformatics How To Write Flexible Documented Tested Python Code For Researc 0
Mastering Python For Bioinformatics How To Write Flexible Documented Tested Python Code For Researc 1
Mastering Python For Bioinformatics How To Write Flexible Documented Tested Python Code For Researc 2
Mastering Python For Bioinformatics How To Write Flexible Documented Tested Python Code For Researc 0
Mastering Python For Bioinformatics How To Write Flexible Documented Tested Python Code For Researc 1
Mastering Python For Bioinformatics How To Write Flexible Documented Tested Python Code For Researc 2

Mastering Python for Bioinformatics; How to Write Flexible, Documented, Tested Python Code for Research Computing 1st Ed

Booknix
43 sales
NaN
$17.22 
 & Instant Download
Payment Methods:
About this item
Note: This is a P D F

Today’s life scientists urgently need bioinformatics skills—but too often, the software tools they rely on are poorly written, rarely maintained, and created by those without formal programming training.
This hands-on guide is here to change that.

Designed for postdocs, researchers, and students in biology, this book teaches you how to harness the power of Python to write clean, tested, and reproducible bioinformatics software. Author Ken Youens-Clark (of Tiny Python Projects, Manning) walks you through modern Python practices that not only solve biological problems but do so with well-documented, maintainable code.

You’ll learn how to:

  • Build command-line Python programs that document and validate user inputs

  • Write tests to verify and refactor scientific code with confidence

  • Apply Python data structures and libraries like Biopython to solve real-world bioinformatics problems

  • Create reproducible workflows using makefiles and scripting best practices

  • Parse key bioinformatics file formats such as FASTA and FASTQ

  • Use regular expressions to identify and extract meaningful patterns in text

  • Leverage Python’s higher-order functions like filter(), map(), and reduce() for efficient data processing

You’ll also work through 14 coding challenges from Rosalind, a popular platform for learning bioinformatics through problem-solving.

This is more than just a programming book—it’s a guide to writing better bioinformatics tools that are robust, readable, and reproducible.

free shipping

Free Shipping

24/7 chat

24/7 Live Chat

30 day returns

Secure Payments