App Development in Biology
Empowering Biologists with the Tools to Develop Custom Apps for Research and Education.
Skills you will gain:
Biology is a data-intensive field, with applications spanning genomics, ecology, bioinformatics, and laboratory research. With the growing need for accessible, user-friendly tools, the development of mobile and web applications has become increasingly important. These apps can aid in everything from data visualization and analysis to collaboration and communication in the lab and field.
This workshop focuses on app development for biology, providing an introduction to coding for biology-specific applications. Participants will be introduced to programming languages like Python, JavaScript, and tools such as BioPython and React Native, enabling them to create applications that are both powerful and intuitive for biologists. Case studies and real-world examples of successful bio-apps will also be presented.
Aim: This workshop aims to teach participants how to develop mobile and web applications tailored for biological research, data analysis, and education. Through hands-on sessions, participants will learn how to create practical apps for tasks such as biological data visualization, genetic analysis, and field research support, empowering biologists to integrate technology into their workflows.
- Understand the basics of mobile and web app development specific to biology.
- Learn to create apps for biological data visualization and analysis.
- Develop basic skills in coding for bioinformatics and biological research applications.
- Explore available tools and frameworks (BioPython, React Native) for biology-related app development.
- Apply app development knowledge to create a basic biology-related app or tool by the end of the workshop.
What you will learn?
Day 1: Introduction to App Development and Python for Biology
- App Development Basics: Importance in biological research, app development process overview.
- Python Basics: Syntax, variables, data types; intro to Pandas and NumPy for data analysis.
- Development Environment Setup: Install Python, libraries, and intro to Flask (web) or Kivy (mobile).
- Hands-on: Write a Python script to analyze basic biological data (e.g., gene sequences).
Day 2: Developing Biological Apps & Using BioPython
- BioPython: Handling biological data (DNA/RNA, protein structures), fetching data from GenBank.
- Building Biological Apps: Intro to Flask/Kivy for web/mobile apps to visualize data.
- Data Integration: Fetch biological data from APIs (e.g., NCBI) and display in app interface.
- Hands-on: Create an app to fetch and display DNA sequence data using Flask/Kivy.
Day 3: Advanced Features, ML for Biology, Final Project
- ML for Biology: Basics of ML, predicting biological data (gene expression, protein function).
- Incorporating ML in Apps: Using Scikit-learn for predictive models, integrating ML in apps.
- Final Project: Develop a complete app (e.g., DNA sequence analyzer, genetic disorder predictor).
Mentor Profile
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Intended For :
- Undergraduate/Postgraduate Degree in Biology, Biotechnology, Bioinformatics, Computational Biology, or related fields.
- Professionals in biology research, bioinformatics, or biological data analysis.
- Developers and Data Scientists interested in creating applications for biology and healthcare sectors.
- Individuals interested in integrating app development skills with biological research or education.
Career Supporting Skills