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A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

An Introduction to Programming for Bioscientists: A Python-Based Primer.

Berk Ekmekci¹, Charles E McAnany¹, Cameron Mura¹

¹Department of Chemistry, University of Virginia, Charlottesville, Virginia, United States of America.

Plos Computational Biology

|June 9, 2016

Summary

Modern biological research heavily relies on computation. This primer introduces Python programming for biosciences, covering essential skills from basic concepts to structural bioinformatics projects.

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Area of Science:

Computational Biology
Bioinformatics
Molecular Biology
Biochemistry

Background:

Computing has transformed biological sciences, making computational tools essential for modern research.
Advances in hardware, software, and algorithms have spurred growth in fields like bioinformatics and structural genomics.
A significant portion of post-genomic biology is now computational biology, requiring researchers to have programming skills.

Purpose of the Study:

To provide a foundational introduction to programming for biosciences using Python.
To equip researchers with indispensable coding skills for contemporary biological research.
To illustrate Python's capabilities through concrete examples and exercises, culminating in a structural bioinformatics project.

Main Methods:

Introduction to Python programming concepts, starting with basic elements like variables.
Step-by-step guidance through coding examples relevant to biological applications.
Inclusion of exercises to reinforce learning and practical application.
Development of a final project in structural bioinformatics.
Supplemental chapters covering advanced topics, including graphical user interface development for sequence analysis.

Main Results:

Demonstration of Python's accessibility for beginners due to its clear syntax and semantics.
Highlighting Python's suitability for object-oriented and other programming paradigms.
Showcasing the extensive functionality of Python libraries for diverse biological domains such as sequence analysis, phylogenomics, and workflow management.
Successful progression from basic programming concepts to complex applications like Hamming distance computation for DNA sequences.

Conclusions:

Python is a versatile and accessible programming language ideal for biosciences.
Proficiency in Python programming is a crucial skill for modern biological researchers.
This primer effectively bridges the gap between basic coding principles and practical bioinformatics applications.