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WELCOME

 

Welcome to the new software package.  This year opens a new chapter in our story in that we begin to explore biology as an information system.  We can do this because the biology literature in combination with mathematics and technology allowed us to assemble and test a robust model for quantitative biology.  Such a model is of upmost importance because it gives us access to the mathematical core of biology.  The core tells us what biology does when, where, and how.

An information science enjoys the remarkable property of being able to deal with complexity at all levels, perhaps being limited only by our imagination, resources, and access to high quality research data.  Complexity is largely a numbers game, one that is played by creating a myriad of interconnected patterns that allow new forms of information to appear and flow.  Biology routinely generates vast amounts of new information by creating new phenotypes - a process that we can now access and duplicate with connection phenotypes. 

Systems biology is an information science.  Run an Internet search on <systems biology> and one finds an excellent collection of ideas.  Indeed, it offers so many promising directions that one is left with the view that it remains a discipline still in search of a mission statement.  This is perfectly understandable for any new discipline and no doubt it will be defined in time largely by the success of its applications.  As an information science, systems biology is of great interest to the Enterprise Biology Software Project because it offers a real world test of our quantitative approach to biology.

To keep things simple, only three goals will be considered this year.  The first will be to assemble a model for systems biology as close to reality as possible, the second to use this model to quantify diseases, and the third to explore new opportunities for creating an individualized medicine.

The software package offers:

  • A progress report containing an introduction to systems biology including theory and practice.
  • An introduction to connection phenotypes as a new complexity tool.
  • A set of software tools designed specifically to capture a broad spectrum of biological changes.
  • Updates of programs and databases.