Python for Bioinformatics with Biopython: Unraveling the Secrets of Biological Data Analysis

What you'll learn
Master Biopython Basics: Students will gain a solid understanding of Biopython's core functionalities, data structures, and essential concepts needed to work wi
Perform Sequence Analysis: Learners will be able to analyze DNA, RNA, and protein sequences, extract relevant information, and perform various sequence manipula
Retrieve and Manage Biological Databases: Students will learn how to retrieve data from online biological databases, process it, and integrate it into their ana
Work with Biological File Formats: Participants will become proficient in reading, writing, and handling different file formats commonly used in bioinformatics,
Explore Genomic data: Learners will explore genomic data and perform analyses related to genes, chromosomes, and genetic variation, using Biopython's tools.
Analyze Protein Structures: Students will learn how to work with protein structures, calculate properties, and perform structural bioinformatics analyses using
Construct Phylogenetic Trees: Participants will understand the principles of phylogenetics, build evolutionary trees, and interpret biological relationships usi
Integrate Machine Learning in Bioinformatics: Learners will explore how to apply machine learning algorithms to solve bioinformatics problems and gain insights
Study Gene Expression using Linux Pipeline: Students will be equipped with the skills to analyze gene expression data using Linux command-line tools, enabling t

Requirements
Basic Python Programming: Learners should have a fundamental understanding of Python programming concepts such as variables, data types, loops, functions, and basic data manipulation.
Biology Basics: Familiarity with basic biological concepts, such as DNA, RNA, proteins, and genetic information, will be helpful for better comprehension of the bioinformatics topics covered in the course.
Computer Literacy: Participants should be comfortable using a computer and basic software applications. No specific operating system is required, as the course will cover both Windows and Linux-based tools.
Text Editor or Integrated Development Environment (IDE): Learners should have access to a text editor or an IDE where they can write and run Python code. Popular choices include VSCode, PyCharm, Jupyter Notebook, or any other text editor of their preference.
Internet Access: Access to the internet is necessary to retrieve biological data from online databases and to install necessary software libraries, including Biopython.
A Desire to Learn: Most importantly, learners should have a keen interest in bioinformatics and a strong desire to explore the fascinating world of computational biology using Python and Biopython.
Lowering the Barrier for Beginners: This course is designed to be beginner-friendly, and no prior experience in bioinformatics or programming is required. The course will start with an introduction to both Python and Biopython, ensuring that learners with little to no programming experience can follow along and gradually build their skills.

https://www.udemy.com/course/python-for-bioinformatics-exploring-biological-data/