Everyday Bioinformatics analysis involves the extensive study and analysis of huge biological datasets, such as sequence alignment and analysis, genome analysis, proteome analysis, phylogenetic analysis, and much more. Python is a great general-purpose scripting language that has become the programming language of choice for most bioinformaticians. 

BioCode is offering an Advanced BioPython for bioinformatics course in which you’ll learn various concepts related to different BioPython modules for reading/writing Bioinformatics files, biological data retrieval from various Bioinformatics databases, sequence analysis, alignment, and much more. Biopython is a set of freely available tools for biological computation written in Python language. It provides various modules and functions for the study and analysis of huge biological datasets. 

This course is for absolute beginners in bioinformatics scripting and you don’t require any prior knowledge of Python programming or even bioinformatics to get started with this course. In this course you will see that by using the modules available within the BioPython package, we don’t have to write long codes to perform a specific task on our biological data, rather we can just call in the built-in functions of BioPython and perform the required task.

This course will include the following sections:

Section 1: Introduction to BioPython

Description: This section will focus on making sure that the students gain an understanding of the BioPython module in Python.

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Understand the BioPython module.
2. Install BioPython.

Section 2: Sequence Analysis

Description: This section will focus on making sure that the students learn about sequence analysis of proteins and DNA and how it is performed using BioPython. 

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Create a Sequence Object Using Bio.Seq Class.
2. Explain How a Sequence Object Behaves like a String.
3. Perform Central Dogma in BioPython.
4. Import UnknownSeq and MutableSeq Objects from Bio.Seq Class.
5. Understand the Alphabets of Biology Using Bio.Alphabet Class.
6. Explain IUPAC Module and Types of Sequence Representation.
7. Concatenate Multiple Sequence Records Using Generic Alphabets.
8. Create Sequence Records Using SeqRecord Module.
9. Utilize the SeqRecord Module to Demonstrate the Representation of FASTA File Within BioPython.
10. Utilize the SeqRecord Module to Demonstrate the Representation of GenBank File Within BioPython.
11. Utilize the Formatting Feature of the SeqRecord Module.
12. Find if there is any Redundancy in the Files They’re Working on Using SeqRecord Module in BioPython.

Section 3: Sequence Data Parsing

Description: This section will focus on making sure that the students learn about parsing/reading sequence data (FASTA/FASTQ) and how it is performed using the SeqIO module in BioPython.

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Read a Sequence File Using SeqIO class.
2. Parse a Sequence File Using SeqIO class.
3. Parse a Compressed Sequence File and Create a Dictionary of Sequences.
4. Write Sequences and SeqRecords into Files.

Section 4: Sequence Data Extraction

Description: This section will focus on making sure that the students learn about sequence data extraction and how it is performed using the SeqIO module in BioPython.

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Extract Annotations and Perform Pattern-wise Sequence Data Extraction Using SeqIO module.

Section 5: Alignment Parsing and Analysis

Description: This section will focus on making sure that the students learn how sequence (protein/DNA) alignment parsing and analysis is performed using the AlignIO module in BioPython.

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Read and Parse a Multiple Sequence Alignment File using AlignIO Module.
2. Write Alignment and Multiple Sequence Alignment Records using AlignIO Module.
3. Convert Alignment Formats.
4. Manipulate Alignments.
5. Align Multiple Sequences Using the ClustalW Python Wrapper.
6. Align Two Sequences Using the paiwise2 Function in BioPython.
7. Read Multiple Sequence Alignment Files of a Particular Format and Map Information of Alignments.
8. Format Alignments.
9. Truncate the Specific Regions from the Entire Alignment (Slice Alignments).

Section 6: BLAST Database Searching

Description: This section will focus on making sure that the students learn how the Bio.Blast module is used to perform the BLAST database search using scripts without accessing webpage.

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Query NCBI BLAST Through Python.

Section 7: Parsing BLAST Results

Description: This section will focus on making sure that the students learn how to parse BLAST results using the Bio.Blast module in BioPython.

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Parse the BLAST Results using the Bio.Blast module.

Section 8: Biological Data Retrieval

Description: This section will focus on making sure that the students learn how to retrieve biological data (sequences/genome assemblies/literature review) using the Bio.Entrez module in BioPython.

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Access ENTREZ Using Python.
2. Get the Summary of Accessions Using Esummary Function of Entrez module in BioPython.
3. Download Complete Records Using EFetch Function.
4. Use EGQuery Function to do Global Queries for Search Count.
5. Search for Database Links of Records Using Elinks.
6. Search the Entrez Database Using ESearch Function.
7. Use ESpell Function to Get the Correct Spellings for your Search Terms.
8. Download GenBank and Entrez Records.
9. Search Taxonomy Database.
10. Download PubMed Articles.

Section 9: Parsing a PDB File Structure

Description: This section will focus on making sure that the students learn how to parse a protein structure (PDB) file structure using the Bio.PDB module in BioPython.

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Read a PDB (3D Structure) File Using Bio.PDB Module.

Section 10: Phylogenetic Analysis

Description: This section will focus on making sure that the students learn how to perform phylogenetic analysis using the Bio.Phylo module in BioPython.

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Calculate the Distance Matrix Between Sequences for Phylogenetic Analysis.
2. Convert Phylogenetic Tree Data Formats.
3. Print Out the Phylogenetic Tree in ASCII.
4. Read Phylogenetic Trees.
5. Visualize and Manipulate Phylogenetic Trees.
6. Write Out Phylogenetic Data.

Section 11: Protein Sequence Analysis

Description: This section will focus on making sure that the students learn how to perform the protein sequence analysis to identify motifs using the Bio.motifs module in BioPython.

Learning Outcomes:  Upon completion of this section, students will be able to:

1. Create a Web Logo of Motifs.
2. Perform MEME Analysis.