Managing Your Biological Data with Python

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A01=Allegra Via
A01=Anna Tramontano
A01=Kristian Rother
AA Aa
AA Aa aA
Atom CA
Author_Allegra Via
Author_Anna Tramontano
Author_Kristian Rother
Bio Import
bioinformatics programming
Biopython applications
Biopython Programming Library
Category=PS
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Command Line
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Hemoglobin Subunit Alpha
Manage Biological Data Using Python
molecular data processing
NCBI Database
NCBI Nucleotide Database
NCBI Server
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P17980 P43686 P35998 P62333 Q99460
PDB Le
Programming In Python
protein structure modelling
PubMed Records
Python for biological data analysis
Python For Life Scientists
Python Interpreter
Python Program
Python Session
Python Shell
Python Tools To Manage The R Package For Statistical Calculations
scientific data visualisation
sequence data analysis
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Text Console
UNIX Command Line
Vice Versa

Product details

  • ISBN 9781138407220
  • Weight: 453g
  • Dimensions: 156 x 234mm
  • Publication Date: 21 Aug 2017
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Take Control of Your Data and Use Python with Confidence

Requiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how to read data from files in different formats, analyze and manipulate the data, and write the results to a file or computer screen.

The first part of the text introduces the Python language and teaches readers how to write their first programs. The second part presents the basic elements of the language, enabling readers to write small programs independently. The third part explains how to create bigger programs using techniques to write well-organized, efficient, and error-free code. The fourth part on data visualization shows how to plot data and draw a figure for an article or slide presentation. The fifth part covers the Biopython programming library for reading and writing several biological file formats, querying the NCBI online databases, and retrieving biological records from the web. The last part provides a cookbook of 20 specific programming "recipes," ranging from secondary structure prediction and multiple sequence alignment analyses to superimposing protein three-dimensional structures.

Tailoring the programming topics to the everyday needs of biologists, the book helps them easily analyze data and ultimately make better discoveries. Every piece of code in the text is aimed at solving real biological problems.

Allegra Via, Kristian Rother, Anna Tramontano

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