Training Course on Bioinformatics Programming using Python (Beginner Level)

This course is intended for those who have little to no prior Python programming knowledge and are curious about using programming techniques to address issues in the field of bioinformatics. The basics of Python programming will be covered, and participants will learn how to use Python libraries that are frequently used in bioinformatics. Participants will learn how to develop Python programs for tasks including sequence analysis, data manipulation, and fundamental bioinformatics techniques throughout the course through actual coding exercises.

Additional focus will be given throughout the course to best practices and real-world applications for Python programming in bioinformatics. Discussions will be encouraged, and participants will be invited to offer their perspectives on various bioinformatics problems.

Participants who successfully complete the course will receive Certificate of Participation. Please note that we extend post-training support for up to 6 months after training.

COURSE OBJECTIVE

By the end of the training course, participants should be able to apply Python programming ideas to fundamental bioinformatics tasks. They should also have the foundation needed to move on to more complex bioinformatics projects. The following outcomes are intended to be accomplished by participants after completing the course:

1. Understanding the fundamentals of Python programming, such as variables, data types, control flow, functions, and file handling.
2. Bioinformatics Introduction: Introduce the subject of bioinformatics, its uses, and the value of programming in resolving biological issues.
3. Sequence Analysis: Acquire knowledge on how to handle DNA, RNA, and protein sequences, carry out fundamental sequence operations, and glean useful data from biological sequences.
4. Data Manipulation: Learn how to manipulate biological data effectively using the NumPy and Pandas packages, as well as Python’s built-in data structures like lists, tuples, and dictionaries.
5. Biopython Library: Get to know the Biopython library and its components so you can programmatically access biological resources, carry out sequence analysis, and run BLAST searches.
6. Data Visualization: Develop plots and charts to display biological data, such as sequence motifs and phylogenetic trees, using Matplotlib.
7. Real-world Bioinformatics Project: Utilize Python to work on a bioinformatics project, solving a particular bioinformatics challenge or doing data analysis on biological data.
8. Excellent Practices in Bioinformatics Programming: Recognize and put into practice excellent practices in bioinformatics programming, such as readability, organization, and the creation of reusable functions.
9. Collaboration and Sharing: Encourage participant collaboration by fostering discussions, exchanging ideas, and learning from one another’s experiences in the context of Python programming and bioinformatics.
10. Resource Awareness: Provide participants with information on numerous online resources, programs, and databases pertinent to Python programming and bioinformatics so they can continue their education when the course is over.

COURSE DURATION

10 Days

WHO SHOULD ATTEND?

It is important to note that this course is intended for novices, thus previous programming or bioinformatics knowledge is not required of participants. However, the course will benefit from having a basic understanding of biology and genetics principles. The course is designed to give participants a solid foundation in Python programming and bioinformatics so they are equipped to take on challenging bioinformatics problems in the real world.

A wide range of people with an interest in both programming and bioinformatics can benefit from this introductory-level training course on Python programming for bioinformatics. This course’s target group includes:

• Biologists and Bioinformatics Researchers: Biologists and researchers in the field of bioinformatics who wish to improve their ability to use Python for data analysis and to automate repetitive chores but who have little to no programming expertise.
• Students and Graduates: Students seeking degrees in biology, bioinformatics, or similar subjects who want to develop programming skills to use them in their future research and professions.
• Computational biologists: Computational biologists looking to switch to Python due to the language’s widespread adoption and strong bioinformatics libraries. These programmers may have prior experience with other languages.
• Data analysts and scientists who are interested in learning about and using Python to analyze biological data.
• Software developers: Those who are interested in bioinformatics and want to expand their skill set to work on bioinformatics projects are considered software developers.
• Healthcare Professionals: Medical professionals that desire to use Python programming for analyzing genetic data, deciphering genomic data, or comprehending bioinformatics analyses. These professionals could be clinicians, researchers, or medical professionals.
• Educators and Instructors: Those who wish to integrate Python programming and bioinformatics into their curricula for teaching.

COURSE MODULE

The course is delivered through the following Modules:

Module 1: Introduction to Python Programming

• Python and its applications in bioinformatics (Introduction)
• Setting up the Python environment (interpreter, IDE, Jupyter Notebook)
• Data types, variables and basic syntax
• Basic operations in Python and Input/output

Module 2: Functions and Control Flow

• if-else, loops (Conditional statements)
• Using functions to write reusable code
• Learning Functions and application in programming
• Implementing a basic sequence analysis function (Exercise)

Module 3: Data Structures in Python

• Dictionaries, tuples, and lists
• Accessing elements and manipulation in data structures
• Manipulation of DNA sequence using data structures (Exercise)

Module 4: File Handling and Data Input/Output

• Reading and writing data to files
• Parsing common bioinformatics file formats (FASTA, GenBank)
• Application: Working with real biological data

Module 5: Python Libraries for Bioinformatics (Part 1)

• BioPython library (Introduction)
• Sequence objects and operations
• Application of Knowledge: Working with real biological databases

Module 6: Python Libraries for Bioinformatics (Part 2)

• Biopython’s modules for sequence analysis (Introduction)
• Sequence alignment and BLAST using Biopython
• Running BLAST searches programmatically (Exercise)

Module 7: Introduction to NumPy and Data Manipulation

• NumPy and its applications in bioinformatics (Introduction)
• NumPy arrays and their operations
• Analyzing biological data using NumPy (Exercise)

Module 8: Introduction to Pandas and Data Analysis

• Pandas and its applications in bioinformatics (Introduction)
• DataFrames: Data manipulation and analysis
• Analyzing gene expression data (Exercise)

Module 9: Introduction to Matplotlib and Data Visualization

• Matplotlib for data visualization (Introduction)
• Data Presentation: Creating plots and charts for biological data
• Visualizing sequence motifs and phylogenetic trees (Exercise)

Module 10: Bioinformatics Project and Wrap-up

• Application of Python skills learned throughout the course
• Application on a bioinformatics project (e.g., sequence alignment, gene expression analysis)
• Presenting results and Discussion
• Recap

General Notes

• The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.
• The participants should be reasonably proficient in English as all facilitation and course materials will be offered in English.
• Upon successful completion of this training, participants will be issued with a certificate.
• The training will be held at Kincaid Training Centre. The course fee covers the course tuition, training materials, two break refreshments and lunch.
• All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.
• Accommodation and airport pickup are arranged upon request. For reservations contact the Training coordinator at Email: training@kincaiddevelopmentcenter.org or Tel: +254 724592901
• This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our Kincaid Training Centre or at a convenient location.

For further inquiries, please contact us on Tel: +254 724592901 or send mail to training@kincaiddevelopmentcenter.org.

Payments are due upon registration. Payment should be sent to our Bank account before commencement of training and proof of payment sent to training@kincaiddevelopmentcenter.org.