Course Content
Introduction to Biopython
0/3
What is Biopython?, Benefits and Applications of Biopython
00:00
Installing Biopython using pip
00:00
Biological data formats
00:00
Sequence Manipulation and Analysis
0/5
Reading and writing Sequences
00:00
Sequence objects and their properties
00:00
Sequence searching and alignment
00:00
Calculating sequence properties
00:00
Subsetting and manipulating sequences
00:00
Sequence Annotation and Features
0/4
Handling sequence annotations and metadata
00:00
Extracting and modifying sequence features
00:00
Parsing and working with GenBank files
00:00
Visualization of sequence features
00:00
Basic Sequence Analysis
0/4
Searching for sequence motifs using regular expressions
00:00
Basic sequence alignment and comparison
00:00
Calculation of sequence similarity and identity
00:00
Finding open reading frames (ORFs)
00:00
Advanced Sequence Analysis
0/6
Performing multiple sequence alignment (MSA)
00:00
Sequence Motifs
00:00
Introduction to Hidden Markov Models (HMMs)
00:00
Phylogenetic Analysis
00:00
Sequence motif discovery and pattern matching
00:00
Protein structure analysis with Bio.PDB
00:00
Working with Biological Databases
0/4
Retrieving data from NCBI databases
00:00
Accessing and querying online biological databases
00:00
Batch retrieval of sequences using Entrez
00:00
Database integration and data management
00:00
Automating Bioinformatics Workflows
0/5
Introduction to Automation in Bioinformatics
00:00
Scripting and automating tasks with Biopython
00:00
Writing efficient and reusable code
00:00
Creating custom functions and modules
00:00
Practical examples and case studies
00:00
Biopython and NGS
0/4
Introduction to NGS data and file formats
00:00
Quality control and filtering of NGS data
00:00
Variant calling and analysis using Biopython
00:00
Introduction to Biopython-compatible NGS tools
00:00
Biopython and Genomic Data Science
0/5
Analyzing genomic data with Biopython
00:00
Genomic data visualization using Biopython and Matplotlib
00:00
Mining and interpreting genomic data
00:00
Machine learning for Genomic data analysis
00:00
Genomic Data Science workflow
00:00
Biopython Fundamentals
About Lesson

Python Requirements

  • Recommend Python version 3.10 from http://www.python.org
  • Biopython is currently supported and tested on the following Python implementations:
  • Python 3.7, 3.8, 3.9, 3.10 and 3.11 – see http://www.python.org
Verifying Python Installation

Biopython is designed to work with Python 2.5 or higher versions. So, it is mandatory that python be installed first. Run the below command in your command prompt −

> python --version

Installing Biopython using pip

It is easy to install Biopython using pip from the command line on all platforms. Type the below command-

>pip install biopython

Verifying Biopython Installation

Now, you have successfully installed Biopython on your machine. To verify that Biopython is installed properly, type the below command on your python console −

C:UsersDELL XPS>python
Python 3.11.3 (tags/v3.11.3:f3909b8, Apr 4 2023, 23:49:59) [MSC v.1934 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import Bio
>>> print(Bio.__version__)
1.81
>>>
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