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🧬 EnzymeML Go

A comprehensive Go implementation of the EnzymeML data exchange format for enzymatic data

Go Version License: MIT


πŸ“‹ Table of Contents

🌟 Overview

Welcome to EnzymeML Go - a robust Go interface for working with EnzymeML documents. EnzymeML is a comprehensive data exchange format specifically designed for enzymatic data, enabling researchers to document, share, and analyze enzymatic experiments in a standardized way.

Why EnzymeML Go?

🎯 Perfect for Database & Web Infrastructure - The key strength of EnzymeML Go lies in powering databases and web applications with enzymatic data while maintaining full compliance with the EnzymeML specification.

✨ Features

EnzymeML Go implements the complete EnzymeML v2 specification, providing you with:

  • πŸ“Š Experimental Documentation: Standardized format for enzymatic experiments
  • βš—οΈ Reaction Conditions: Capture detailed reaction conditions and measurements
  • πŸ“ˆ Kinetic Models: Define and work with kinetic models and parameters
  • πŸ”„ Data Exchange: Seamless data exchange between platforms and modeling tools
  • 🌐 FAIR Compliance: Ensures Findable, Accessible, Interoperable, Reusable data principles
  • πŸ—„οΈ Database Ready: Optimized for database storage and web applications

πŸš€ Installation

Get started with EnzymeML Go in seconds:

go get github.com/enzymeml-go

Requirements

  • Go 1.19+ - Ensure you have a recent version of Go installed
  • Modern Go modules - This package uses Go modules for dependency management

πŸ“– Usage

Quick Start

package main

import (
    "fmt"
    "github.com/enzymeml-go"
)

func main() {
    // Your EnzymeML Go code here
    fmt.Println("Welcome to EnzymeML Go!")
}

πŸ—„οΈ Database Example

For a comprehensive example of how to use EnzymeML Go to create an enzymatic data database and power web applications, check out our detailed example:

πŸ‘‰ Database Example

This example demonstrates:

  • Setting up an EnzymeML-compliant database
  • Storing and retrieving enzymatic data
  • Web application integration
  • Best practices for data management

🀝 Contributing

We welcome contributions from the community! Please feel free to submit a pull request.

πŸ“„ License

This project is licensed under the MIT License - see the LICENSE file for details.


Made with ❀️ by the EnzymeML Team

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