#!/usr/bin/env python
# coding: utf-8

# **Source of the materials**: Biopython Tutorial and Cookbook (adapted)

# <img src="images/biopython.jpg">

# # Introduction

# ## What is Biopython?

# The Biopython Project is an international association of developers of freely available Python (http://www.python.org) tools for computational molecular biology. Python is an object oriented, interpreted, flexible language that is becoming increasingly popular for scientific computing. Python is easy to learn, has a very clear syntax and can easily be extended with modules written in C, C++ or FORTRAN.
# 
# The Biopython web site (http://www.biopython.org) provides an online resource for modules, scripts, and web links for developers of Python-based software for bioinformatics use and research. Basically, the goal of Biopython is to make it as easy as possible to use Python for bioinformatics by creating high-quality, reusable modules and classes. Biopython features include parsers for various Bioinformatics file formats (BLAST, Clustalw, FASTA, Genbank,...), access to online services (NCBI, Expasy,...), interfaces to common and not-so-common programs (Clustalw, DSSP, MSMS...), a standard sequence class, various clustering modules, a KD tree data structure etc. and even documentation.
# 
# Basically, we just like to program in Python and want to make it as easy as possible to use Python for bioinformatics by creating high-quality, reusable modules and scripts.

# ## What can I find in the Biopython package

# The main Biopython releases have lots of functionality, including:
# 
# - The ability to parse bioinformatics files into Python utilizable data structures, including support for the following formats:
#   - Blast output – both from standalone and WWW Blast
#   - Clustalw
#   - FASTA
#   - GenBank
#   - PubMed and Medline
#   - ExPASy files, like Enzyme and Prosite
#   - SCOP, including ‘dom’ and ‘lin’ files
#   - UniGene
#   - SwissProt
# - Files in the supported formats can be iterated over record by record or indexed and accessed via a Dictionary interface.
# - Code to deal with popular on-line bioinformatics destinations such as:
#   - NCBI – Blast, Entrez and PubMed services
#   - ExPASy – Swiss-Prot and Prosite entries, as well as Prosite searches
# - Interfaces to common bioinformatics programs such as:
#   - Standalone Blast from NCBI
#   - Clustalw alignment program
#   - EMBOSS command line tools
# -A standard sequence class that deals with sequences, ids on sequences, and sequence features.
# - Tools for performing common operations on sequences, such as translation, transcription and weight calculations.
# - Code to perform classification of data using k Nearest Neighbors, Naive Bayes or Support Vector Machines.
# - Code for dealing with alignments, including a standard way to create and deal with substitution matrices.
# - Code making it easy to split up parallelizable tasks into separate processes.
# - GUI-based programs to do basic sequence manipulations, translations, BLASTing, etc.
# - Extensive documentation and help with using the modules, including this file, on-line wiki documentation, the web site, and the mailing list.
# - Integration with BioSQL, a sequence database schema also supported by the BioPerl and BioJava projects.
# 
# We hope this gives you plenty of reasons to download and start using Biopython!

# ## About these notebooks

# These notebooks were prepared on Python 3 for Project Jupyter 4+ (formely IPython Notebook). Biopython should be installed and available (v1.66 or newer recommended).
# 
# You can check the basic installation and inspect the version by doing:

# In[1]:


import Bio
print(Bio.__version__)


# In[ ]: