Introduction to Python for genetics

Name: Introduction to Python for genetics
Rating: 4.5 (330 reviews)

Learn how to simulate and model basic problems of genetics in the Programming language Python!

Created byGuilherme Matos Passarini, phD

Last updated 11/2023

English

English [Auto],

What you'll learn

You will learn how to model genetics problems with Python
The basic mendelian genetics
DNA replication
DNA transcription
DNA translation
The Hardy-Weinberg Theorem
The main variable types
User input
Arithmetic operations
Relational and logical operators
Conditional statements
For and while loops
Tuples, lists and dictionaries
Functions
Modules
File I/O
How to calculate the frequency of recombinant genotypes and estimate the gene distance
How to model the transcription process
How to model the translation process
How to solve a population genetics problem

Course content

12 sections • 66 lectures • 4h 18m total length

Course overview/introduction1:24
About the speed of the lectures0:10

Basic concepts5:01
The gene-protein flow and building blocks4:45
Explore how DNA, RNA, and proteins flow from gene to function, contrasting prokaryotic and eukaryotic genomes, transcription and splicing, and the roles of nucleotides and amino acids.
Inheritance and recombination4:56
The transcription process3:17
The translation process3:32
Explore the translation process, where messenger rna is read by ribosomes, aided by transfer rna, to assemble amino acids into polypeptides according to the genetic code.
Population genetics: the Hardy-Weinberg Theorem4:23
Basic concepts of genetics

Main variables and types4:57
Arithmetic operators5:11
User input2:15
Variables, types, user input, arithmetics
Exercises2:01
Solution - Estimating recombination frequency3:32
Erratum0:10
In the previous 'solution' lecture, until minute 0:40, I show the formula of recombination frequency to be like this:

rec1 + rec2 + nonrec1 + nonrec2 / rec1 + rec2

After 0:40, the formula is inverted to rec1 + rec2 /rec1 + rec2 + nonrec1 + nonrec2, which is the correct formula
Solution - Calculating allele frequencies3:41

Strings - concept and methods8:21
String manipulation
Exercises1:44
Solution: finding start and termination codons3:39
Locate the start and termination codons in an RNA sequence and extract the open reading frame using Python, demonstrating the positions and the sequence between them.
Solution: manipulating a DNA string1:34
Convert a lowercase dna string to uppercase, extract characters five through ten, and transcribe dna to rna by replacing t with u.

Relational/logical operators4:44
Conditional statements5:11
Nested and complex conditions6:08
Logical operators and conditional statements
Exercises2:05
Practice with relational operators and conditional statements through two exercises: a biomolecule classifier for DNA, RNA, or neither, and a polypeptide check for methionine and more than 10 amino acids.
Biomolecule classifier3:18
Polypetide sequence analysis with string manipulation2:54

The for loops5:27
Learn how to use for loops in Python to iterate over numbers, strings, and lists, understand range end is exclusive, and prepare for nested for loops.
The "nested" for loops2:30
The while commands7:27
Explore the while loop in Python, including counting numbers and iterating strings by index. Learn how to use true loops, conditions, and break for input validation.
Loops
Exercises2:12
Solution - base pairing verification3:10
Solution - Simulating the transcription process2:16
Solution - Hamming distance2:47
Learn to compute the Hamming distance between two equal-length DNA strings using a while loop in Python, and calculate their similarity percentage.

Tuples6:39
Lists6:30
Dictionaries7:56
Collections
Exercises2:46
Solution - Transcription process with dictionaries2:23
Solution - Modelling the translation process2:39
Write code that translates an RNA sequence into a polypeptide chain using a codon dictionary and a loop that processes codons until a stop codon terminates.
Solution - challenge 1: RNA splicing2:49
Build a python tool to locate ORFs in a pre messenger RNA sequence by scanning for start codons, collecting sequences until stop codons, and listing ORFs.

Functions: definition and declaration5:46
Functions: optional parameters, scope and docstrings6:45
Functions
Exercises5:18
Solution - A function that extracts the proportion (%) of AT's/CG's2:42
Solution - function that calculates the recombination frequency3:18
Write a Python function to estimate recombination frequency from recombinant and non recombinant genotypes, with parameters for each count and an optional decimal places argument.
Solution - Challenge 1: Hardy Weinberg Theorem - interpretation of the results8:23

Requirements

A basic knowledge of genetics is desirable, but the course has a brief review of genetics at the beginning

Description

Many students and professionals of biosciences are not familiar with programming. However, the increasing amount of biological data generated every year, along with advances in biotechnology and the increasing role of informatics in life sciences makes the programming knowledge essential for biologists, biotechnologists, and so on! In this introductory course, you will learn how to model simple genetics problems using the programming language Python. First, you will learn how to implement the commands or data structures in Python. And Finally, we will model some problems in the field of genetics using the knowledge acquired so far.

Since this is an introductory course, we will not use third-party libraries, such as Biopython, matplotlib, pandas, etc., but only the built-in commands, modules, and data structures.

In the first section of the course, we have a very brief introduction to refresh some concepts of genetics, such as genes, alleles, frequency, etc... In the second part of the course, you'll learn the basic commands, data structures, and functions of Python. In these chapters, you must apply the knowledge acquired so far in the chapter to solve some problems related to genetics in Python! There are more than 20 exercises and challenges to be solved throughout the course!

Therefore, if you want to:

Learn to think algorithmically
Model problems of genetics in a programming language
Learn how to use the most popular programming languages to model problems of biology

...this course is for you!

Who this course is for:

Biologists/biotechnologists
Biology/biotechnologists students
Programmers or computer scientists curious to understand the possible application of Python in genetics
Python and/or genetics enthusiasts

Introduction to Python for genetics

What you'll learn

Explore related topics

Course content

Introduction to the course2 lectures • 2min

####PART 1: BASIC GENETICS ######6 lectures • 26min

#####PART 2: PROGRAMMING WITH PYTHON #####3 lectures • 5min

Variables and types7 lectures • 22min

Strings and text manipulation4 lectures • 15min

Relational/logical operators and conditional statements6 lectures • 24min

For and while loops7 lectures • 26min

Tuples, lists and dictionaries7 lectures • 32min

Functions6 lectures • 32min

Modules7 lectures • 29min

Requirements

Description

Who this course is for: