Python for Bioinformatics · From Zero to Biological DataPython for Bioinformatics

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Python for Bioinformatics

From Zero to Biological Data

14 modules187 lessons17 h 15 min

No prior experience needed

Progress0%

0/187 lessons

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What you'll learn

Read and write simple Python programs
Store text and numbers in variables
Make programs that think and repeat work
Represent DNA and protein sequences as data
Compute real biological quantities like GC content

Your path

0. Welcome to Programming30 min0/9

0.1 · What is programming?
0.2 · What is Python?
0.3 · How this course works
0.4 · Your first Python instruction
0.5 · Code editor and output
0.6 · What does "Run code" mean?
0.7 · Reading simple Python
0.8 · Your first mistake
0.9 · Module review

1. Your First Python Programs1 h 10 min0/13

1.1 · print()
1.2 · Text and strings
1.3 · Numbers
1.4 · Simple calculations
1.5 · Comments
1.6 · Variables
1.7 · Changing variables
1.8 · Variable names
1.9 · Basic types
1.10 · Combining text and values
1.11 · f-strings
1.12 · Your first errors
1.13 · Module challenge

2. Making Programs Think1 h 5 min0/12

2.1 · Questions with True and False
2.2 · Comparison operators
2.3 · if
2.4 · Indentation
2.5 · else
2.6 · elif
2.7 · and
2.8 · or
2.9 · not
2.10 · Combining conditions
2.11 · Common conditional mistakes
2.12 · Module challenge

3. Repeating Work1 h 5 min0/12

3.1 · Why computers repeat tasks
3.2 · for loops
3.3 · range()
3.4 · Repeating calculations
3.5 · Looping through text
3.6 · Looping through DNA
3.7 · while loops
3.8 · break
3.9 · continue
3.10 · Nested repetition, introductory
3.11 · Common loop mistakes
3.12 · Module challenge

4. Working with Text1 h 10 min0/13

4.1 · Strings in more detail
4.2 · String length
4.3 · Indexing
4.4 · Zero-based indexing explained
4.5 · Negative indexing
4.6 · Slicing
4.7 · Searching text
4.8 · count()
4.9 · replace()
4.10 · upper() and lower()
4.11 · Cleaning text
4.12 · Combining operations
4.13 · Module challenge

5. Organizing Data1 h 10 min0/13

5.1 · Why we need collections
5.2 · Lists
5.3 · Reading list elements
5.4 · Changing lists
5.5 · append()
5.6 · remove()
5.7 · len()
5.8 · Looping through lists
5.9 · Tuples
5.10 · Dictionaries
5.11 · Dictionary keys and values
5.12 · Sets
5.13 · Module challenge

6. Functions1 h 5 min0/12

6.1 · Why functions exist
6.2 · Creating your first function
6.3 · Calling a function
6.4 · Parameters
6.5 · Multiple parameters
6.6 · return
6.7 · return vs print
6.8 · Local variables
6.9 · Reusing functions
6.10 · Functions with biological data
6.11 · Debugging functions
6.12 · Module challenge

7. Files, Paths and Errors1 h 20 min0/15

7.1 · What is a file?
7.2 · Files and folders
7.3 · File extensions
7.4 · What is a path?
7.5 · Paths conceptually
7.6 · Reading a text file
7.7 · Writing a text file
7.8 · with open(...)
7.9 · Why files should be closed
7.10 · Exceptions
7.11 · try / except
7.12 · FileNotFoundError
7.13 · ValueError
7.14 · Debugging strategies
7.15 · Module challenge

8. Python Meets DNA1 h 30 min0/17

8.1 · Biology becomes data
8.2 · DNA as a string
8.3 · Sequence length
8.4 · Counting A/T/G/C
8.5 · Validating sequences
8.6 · GC content
8.7 · Complement
8.8 · Reverse
8.9 · Reverse complement
8.10 · DNA to RNA
8.11 · Codons
8.12 · Translation concept
8.13 · Stop codons
8.14 · Searching motifs
8.15 · Mutations as string changes
8.16 · Comparing sequences
8.17 · Mini project: DNA Analyzer

9. Biological File Formats1 h 10 min0/13

9.1 · What is FASTA?
9.2 · Anatomy of a FASTA record
9.3 · Headers
9.4 · Sequences
9.5 · Reading one FASTA record
9.6 · Multiple FASTA sequences
9.7 · A simple FASTA parser
9.8 · What is FASTQ?
9.9 · FASTQ structure
9.10 · What is a quality score?
9.11 · Quality scores conceptually
9.12 · TSV / CSV biological data
9.13 · Module challenge

10. Scientific Python1 h 25 min0/16

10.1 · What is a Python library?
10.2 · import
10.3 · Why scientists use libraries
10.4 · NumPy introduction
10.5 · NumPy arrays
10.6 · Basic calculations
10.7 · pandas introduction
10.8 · DataFrames
10.9 · Columns and rows
10.10 · Filtering biological data
10.11 · Summary statistics
10.12 · Matplotlib introduction
10.13 · First plot
10.14 · Labels and axes
10.15 · Biological measurements
10.16 · Module project

11. Biopython1 h 20 min0/15

11.1 · What is Biopython?
11.2 · Why use a library?
11.3 · Bio.Seq
11.4 · Seq objects
11.5 · complement()
11.6 · reverse_complement()
11.7 · transcription
11.8 · translation
11.9 · SeqRecord
11.10 · SeqIO
11.11 · Reading FASTA
11.12 · Reading multiple records
11.13 · FASTQ
11.14 · Basic sequence statistics
11.15 · Module challenge

12. Practical Bioinformatics1 h 15 min0/14

12.1 · Processing many sequences
12.2 · Filtering by length
12.3 · Filtering by GC
12.4 · Detecting invalid sequences
12.5 · Searching motifs
12.6 · Regular expressions: gentle intro
12.7 · Counting motifs
12.8 · Dictionaries and sequences
12.9 · Building summary tables
12.10 · Exporting CSV
12.11 · Creating plots
12.12 · Reusable analysis functions
12.13 · Pipeline thinking
12.14 · Module project

13. Final Project2 h0/13

13.1 · Understand the problem
13.2 · Design the program
13.3 · Read the input
13.4 · Validate sequence
13.5 · Calculate statistics
13.6 · Build functions
13.7 · Process multiple sequences
13.8 · Create table
13.9 · Plot
13.10 · Export results
13.11 · Final integration
13.12 · Final challenge
13.13 · Course completion