Math Biotech

Mathematics learning application for biotechnology students, designed to be published as a responsive web app, an installable PWA and native mobile packages from one shared codebase.

The project combines interactive mathematical learning, biotechnology-oriented examples, three-dimensional visualizations and a REST API for deterministic calculations and study records.

Project status

Active development — public transition repository

The source is publicly visible, but a final open-source license has not yet been selected. Until a LICENSE file is added, public visibility alone does not grant general reuse rights.

Current capabilities

• Biotechnology-oriented mathematical lessons and examples
• Matrix addition, multiplication, determinant and inverse workflows
• Exam-performance tracking and statistics
• Formula rendering with KaTeX
• Interactive 3D content through Three.js
• AI-assisted explanations
• Installable PWA support
• Android packaging through Capacitor
• REST API for calculations and study integrations

Technology

Client

• React 19 and TypeScript
• Vite and Tailwind CSS
• Math.js and KaTeX
• Three.js, React Three Fiber and Drei
• Framer Motion
• Vite PWA
• Capacitor for Android
• Vitest and Testing Library

Backend

• Node.js and Express
• TypeScript
• Environment-based server configuration

Architecture

Web / PWA / Capacitor mobile client
                 │
                 ▼
          Versioned REST API
                 │
       ┌─────────┴─────────┐
       ▼                   ▼
Deterministic math     Study records and
operations             controlled AI gateway

The web, PWA and mobile builds should share the same course logic. Platform-specific capabilities belong behind explicit adapters rather than in separate copies of the application.

Web development

Install dependencies and start the client:

npm install
npm run dev

Create and preview a production build:

npm run build
npm run preview

Backend development

cd server
npm install
npm run dev

The development API is available by default at:

http://localhost:5000

Build and start the compiled backend:

npm run build
npm start

Backend details are available in server/README.md.

Mobile development

The repository contains Capacitor Android support. After a successful web build, synchronize the native project and open it in Android Studio:

npm run build
npx cap sync android
npx cap open android

Native releases should be generated from tagged commits through CI. Downloadable APK files should include release notes and checksums.

AI security transition

The current AI interface includes a bring-your-own-key browser flow. Browser-persisted API keys are not an acceptable production design and must be removed before an official hosted release.

The target design is an authenticated backend AI gateway with:

• No provider credential in the web or mobile bundle
• No API key stored in localStorage
• Per-user authorization
• Input-size and rate limits
• Usage quotas and cost monitoring
• Provider timeout handling
• Explicit response schemas
• Safe Markdown rendering
• Minimal logs that exclude private learning content

AI explanations must remain secondary to deterministic mathematical verification.

Testing priorities

• Matrix and numerical calculations
• Invalid and boundary inputs
• Formula parsing and rendering
• Exam scoring and progress calculations
• API request validation
• AI response-schema handling
• Consistency between web and mobile builds

Run the existing client tests with:

npx vitest run

Run the current backend API check from server/:

npm test

Open-source release requirements

Before declaring the project fully open source:

• Select and add an open-source license.
• Audit the current tree and full Git history for credentials and private files.
• Remove browser-persisted API-key handling.
• Route production AI calls through the backend.
• Consolidate the roles of Math-Biotech-App and Math-Biotech-Project.
• Add CI for tests, builds, dependency review and secret scanning.
• Add CONTRIBUTING.md, SECURITY.md and a code of conduct.
• Document the license and source of course content and visual assets.
• Publish reproducible web and Android release procedures.
• Add privacy, export and account-deletion documentation where user data is stored.

The shared strategy for Math, Botany and Organic Chemistry is documented in the private Inmerse workspace roadmap.

Scientific and educational responsibility

Mathematical results and AI-generated explanations should be independently checked before academic, laboratory, clinical or professional use. Simplified models should be identified as models rather than complete representations of living systems.

Author

Developed by Halil Ibrahim Ozturk.