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rxncon

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Your rating: None Average: 5 (2 votes)

The complexity of cellular networks is an outstanding challenge for documentation, visualisation and mathematical modelling. In this project, we develop a new way to describe these networks that minimises the combinatorial complexity and allows an automatic visualisation and export of mathematical (ODE/rulebased) models.

Features:

  • Automatic visualiztion with Cytoscape.
  • Automatic generation of rule based models for BioNetGen.
  • Storage of biological facts that can be used for modelling.

MeVisLab

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Your rating: None Average: 4.5 (4 votes)

MeVisLab represents a platform for image processing research and development with a focus on medical imaging. It allows fast integration and testing of new algorithms and the development of application prototypes that can be used in clinical environments.

OPAL

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Your rating: None Average: 4 (10 votes)

OPAL Is a full stack web framework for building health care applications.

OPAL encourages rapid development, and elegant, pragmatic design.

Focussed on health care, it builds on years of research and design to
help you in building your app. It's free and open source.

AuShadha

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Your rating: None Average: 3.9 (27 votes)

AuShadha (औषध): Means medicine in Sanskrit.

This is a Open Source Electornic Medical Records (EMR) & Public Health Management System for Small Clinics. It might be even suited for speciality medical practice after some customisation.

It is developed with Python, Django and Dojo. Because its developed with Django, it supports whatever database Django supports.

AuShadha code is licensed under GNU-GPL Version 3. Django, Dojo, Icons and other thrid party modules are licensed as per their authors.