Bioinformatics Internship Task Portal Access 03
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Welcome to the Internship Task Portal of Embedded systems technologies .
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🧬 Python for Bioinformatics – Internship Update
The Python for Bioinformatics Internship is designed to help students build strong foundations in programming while applying it to real-world biological data analysis. This program focuses on combining Python skills with bioinformatics concepts such as DNA sequence analysis, string manipulation, and data processing.
Throughout the internship, participants will:
- Learn Python basics tailored for biological applications
- Work with DNA/RNA sequences using string operations
- Perform sequence analysis like GC content and base counting
- Handle bioinformatics file formats (such as FASTA)
- Build a mini project to apply their learning
Each task includes:
- 📺 Session-based learning
- 📝 Notes preparation
- 💻 Hands-on coding practice
- 📤 Submission via Google Forms
By the end of the internship, students will gain practical experience in computational biology and develop skills useful for careers in bioinformatics, data science, and research.
TASK 1: Reading Multiple GenBank Files and Counting Features
🎯 Objective:
Learn how GenBank files store biological information and understand how bioinformaticians analyze multiple genomic records to extract and count biological features.
🎥 Session:
Session 01 – Reading Multiple GenBank Files and Count Features
Session Link: click here to access
📝 Task:
Write Notes On:
- Introduction to GenBank Files
- Structure of a GenBank Record
- Biological Features in GenBank
- Gene Annotations
- CDS (Coding Sequences)
- Feature Extraction Methods
- Importance of GenBank Databases
- Applications in Genomics Research
🔬 Practice / Research:
- Research the purpose of GenBank.
- Explain the difference between sequence data and annotation data.
- List common biological features stored in GenBank records.
📘 Assignment:
Prepare a report (250–350 words):
“Importance of GenBank Files in Bioinformatics and Genomic Research.”
📂 Internship Task Completion Status Form
After completing this task, interns must upload:
✅ Session Notes
✅ Assignment Report
✅ Research Findings
✅ Practice Work (if applicable)
📤 Form Link: https://forms.gle/dcfdpoDgksgP9KUY8
TASK 2: How to Extract Sequences from a FASTA Using Python
🎯 Objective:
Understand FASTA file formats and learn how Python can be used to extract biological sequences for further analysis.
🎥 Session:
Session 02 – How to Extract Sequences from a FASTA Using Python
Session Link: click here to access
📝 Task:
Write Notes On:
- What is a FASTA File?
- Structure of FASTA Format
- DNA Sequences
- RNA Sequences
- Protein Sequences
- Sequence Extraction Techniques
- Python Applications in Bioinformatics
- Importance of Sequence Analysis
🔬 Practice / Research:
- Research biological databases that use FASTA format.
- Explain why sequence extraction is important.
- List applications of FASTA files in genomics.
📘 Assignment:
Write a report (300–400 words):
“Role of FASTA Files and Python in Modern Bioinformatics.”
💻 Mini Practical:
Create a sample FASTA file containing 3 DNA sequences and explain how each sequence could be analyzed.
📂 Internship Task Completion Status Form
After completing this task, interns must upload:
✅ Session Notes
✅ Assignment Report
✅ Practical Work
✅ Research Activity
📤 Form Link: https://forms.gle/dcfdpoDgksgP9KUY8
TASK 3: Python List Operations for Bioinformaticians
🎯 Objective:
Learn how Python lists are used to store, manage, and analyze biological data efficiently.
🎥 Session:
Session 03 – Python List Operations for Bioinformaticians
Session Link: click here to access
📝 Task:
Write Notes On:
- Introduction to Python Lists
- Creating Lists
- Accessing Elements
- List Indexing
- List Slicing
- Adding and Removing Elements
- Sorting Lists
- Applications in Bioinformatics
🔬 Practice / Research:
- Explain why lists are useful in biological data analysis.
- Research examples where genomic data is stored in lists.
- Compare lists and arrays in Python.
📘 Assignment:
Prepare a report (250–350 words):
“Applications of Python Lists in Bioinformatics and Computational Biology.”
💻 Mini Practical:
Create a list containing 10 gene names and perform the following:
- Access the first gene
- Access the last gene
- Extract genes 3–7
- Sort the list alphabetically
Take screenshots or provide outputs.
📂 Internship Task Completion Status Form
After completing this task, interns must upload:
✅ Session Notes
✅ Assignment Report
✅ Practical Activity
✅ Screenshots of Output
📤 Form Link: https://forms.gle/dcfdpoDgksgP9KUY8
TASK 4: Introduction to Tuples in Python for Bioinformaticians
🎯 Objective:
Understand Python tuples and their applications in storing fixed biological data structures.
🎥 Session:
Session 04 – Introduction to Tuples in Python for Bioinformaticians
Session Link: click here to access
📝 Task:
Write Notes On:
- What are Tuples?
- Tuple Syntax
- Creating Tuples
- Accessing Tuple Elements
- Differences Between Lists and Tuples
- Immutable Data Structures
- Applications in Bioinformatics
- Advantages of Tuples
🔬 Practice / Research:
- Compare Python Lists and Tuples.
- Explain why immutable data structures are useful.
- Research examples of biological information stored as tuples.
📘 Assignment:
Prepare a report (300–400 words):
“Importance of Tuples in Bioinformatics Programming.”
💻 Mini Practical:
Create a tuple containing:
- Gene Name
- Organism Name
- Sequence Length
- Chromosome Number
Explain why a tuple may be preferred over a list for storing this information.
📂 Internship Task Completion Status Form
After completing this task, interns must upload:
✅ Session Notes
✅ Assignment Report
✅ Practical Activity
✅ Screenshots or Outputs
📤 Form Link: https://forms.gle/dcfdpoDgksgP9KUY8
🎓 MINI PROJECT
Project Title:
Python-Based Biological Sequence Analysis
Objective:
Apply Python programming concepts to manage and analyze biological sequence data.
Project Tasks:
- Create a sample FASTA dataset
- Store sequences using lists and tuples
- Extract sequence information
- Calculate sequence lengths
- Organize biological records
Final Report (500–800 Words)
Include:
- Introduction
- Dataset Description
- Python Concepts Used
- Analysis Performed
- Results
- Conclusion
📂 Final Project Submission Form
After completing the project, interns must upload:
✅ Final Project Report
✅ Python Code Files
✅ Screenshots of Output
✅ Dataset Used
✅ Research Notes