Commit 32174425 authored by Elad Noor's avatar Elad Noor

adding citation ref and link to component-contribution on GitHub

parent 161cdaf3
# equilibrator-api
A command-line API with minimal dependencies for calculation of standard thermodynamic potentials of biochemical reactions using the data found on [eQuilibrator](http://equilibrator.weizmann.ac.il/).
A command-line API with minimal dependencies for calculation of standard thermodynamic potentials of biochemical reactions using the data found on [eQuilibrator](http://equilibrator.weizmann.ac.il/).
Does not require any network connections.
# Current Features
# Current Features
* Example scripts for singleton and bulk calculations.
* Calculation of standard Gibbs potentials of reactions.
* Calculation of standard Gibbs potentials of reactions (together with confidence intervals).
* Calculation of standard reduction potentials of half-cells.
To access more advanced features, such as adding new compounds that are not available in the KEGG database,
try using our full-blown [Component Contribution](https://github.com/eladnoor/component-contribution)
package.
# Cite us
If you plan to use results from equilibrator-api in a scientific publication,
please cite our paper:
Noor E, Haraldsdóttir HS, Milo R, Fleming RMT. Consistent estimation of Gibbs energy using component contributions. PLoS Comput Biol. 2013;9: e1003098.
# Example Usage
Import the API and create an instance. Creating the EquilibratorAPI class instance reads all the data that is used to calculate thermodynamic potentials of reactions.
Import the API and create an instance. Creating the EquilibratorAPI class instance reads all the data that is used to calculate thermodynamic potentials of reactions.
```python
from equilibrator_api import EquilibratorAPI, Reaction
......@@ -37,12 +49,12 @@ Now we know that the reaction is "kosher" and we can safely proceed to calculate
# You control the pH and ionic strength!
# ionic strength is in Molar units.
dG0_prime, dG0_uncertainty = eq_api.dG0_prime(
rxn, pH=6.5, ionic_strength=0.2)
rxn, pH=6.5, ionic_strength=0.2)
print u"dG0' = %.1f \u00B1 %.1f kJ/mol\n" % (
dG0_prime, dG0_uncertainty)
```
You can also calculate the [reversibility index](https://doi.org/10.1093/bioinformatics/bts317) for this reaction.
You can also calculate the [reversibility index](https://doi.org/10.1093/bioinformatics/bts317) for this reaction.
```python
ln_RI = rxn.reversibility_index(pH=6.5, ionic_strength=0.2)
......@@ -51,7 +63,7 @@ print u'ln(Reversibility Index) = %.1f\n' % ln_RI
The reversibility index is a measure of the degree of the reversibility of the reaction that is normalized for stoichiometry. If you are interested in assigning reversibility to reactions we recommend this measure because 1:2 reactions are much "easier" to reverse than reactions with 1:1 or 2:2 reactions. You can see the paper linked above for more information.
# dependencies:
# Dependencies:
- python 2.7
- numpy (preferably >= 1.12.0)
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment