https://github.com/djinnome/biohacker

Automatically exported from code.google.com/p/biohacker
https://github.com/djinnome/biohacker

Last synced: 21 days ago
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Automatically exported from code.google.com/p/biohacker

• Host: GitHub
• URL: https://github.com/djinnome/biohacker
• Owner: djinnome
• Created: 2015-03-14T14:20:22.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2015-07-01T19:29:16.000Z (over 9 years ago)
• Last Synced: 2024-11-09T08:05:11.567Z (3 months ago)
• Language: Common Lisp
• Size: 5.3 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

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Automatically exported from code.google.com/p/biohacker

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_Mistakes are the portals of discovery._ James Joyce (1882-1941)

A metabolic network of an organism is defined as a set of all biochemical reactions catalyzed by the enzymes encoded in its genome.  During the reconstuction of an organism's metabolic network, several kinds of inference problems can arise:  

  * Inferring instance reactions from generic reactions

    * e.g. `An alcohol + NAD+ --> an aldehyde + NADH` is instantiated to `ethanol + NAD+ --> acetaldehyde + NADH`

  * Inferring missing reactions and transporters from experimentally observed phenotypes

    * e.g. Metabolic network is unable to produce essential compounds necessary for growth from a known minimal nutrient media

  * Inferring reactions to remove based on experimentally observed phenotypes.

    * e.g. Metabolic network can produce all compounds sufficient for growth even after the removal of an essential gene

Because of these issues, manually reconstructing metabolic networks from annotated genomes is currently a time-consuming, error-prone process.

We develop `BioHacker`, a debugger for metabolic networks. `BioHacker` not only detects these issues, but also generates explanations as to where the problems lie and generates hypotheses for how to fix them.

  * Read the [BioHacker paper (PDF)](http://biohacker.googlecode.com/svn/docs/biohacker.pdf).

  * Check out the [source code](http://code.google.com/p/biohacker/source/list).