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Related Experiment Video

Updated: Feb 7, 2026

Shock Wave Application to Cell Cultures

Shock Wave Application to Cell Cultures

Published on: April 8, 2014

WAVES: a web application for versatile enhanced bioinformatic services.

Marc Chakiachvili^1,2, Sylvain Milanesi¹, Anne-Muriel Arigon Chifolleau¹

¹LIRMM UMR 5506 - CNRS & Université de Montpellier, Montpellier, France.

Bioinformatics (Oxford, England)

|July 28, 2018

Summary

This summary is machine-generated.

WAVES is a reusable web application for integrating bioinformatics tools, offering services via web pages, forms, and a RESTful API. It supports various computational environments like Galaxy for efficient bioinformatic software implementation.

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Area of Science:

Bioinformatics
Computational Biology
Web Services

Background:

Bioinformatic tool integration is crucial for efficient data analysis.
Implementing and accessing diverse bioinformatics software presents challenges.
There is a need for standardized methods to serve bioinformatic tools.

Purpose of the Study:

To present WAVES, a web application for seamless bioinformatic tool integration.
To provide multiple access points for bioinformatic services.
To enable flexible computational resource utilization for bioinformatics.

Main Methods:

Developed as a reusable web application using Django (Python framework).
Automated service generation for bioinformatic software.
Implementation of web pages, embeddable web forms, and a RESTful API.
Support for distributed computation environments, including Galaxy.

Main Results:

WAVES facilitates the creation of accessible services for any bioinformatic software.
Services are available through web interfaces and a programmatic API.
The application supports computations on various platforms, enhancing flexibility.
WAVES is portable, requiring only a Python installation.

Conclusions:

WAVES offers an efficient and versatile solution for bioinformatic tool integration and service delivery.
The application promotes wider accessibility and usability of bioinformatics resources.
Its design supports scalability and adaptability in computational biology workflows.