BioCyc Interface Demo
This notebook is a quick demo of a BioCyc Web API I’ve released for Python. While incomplete the API offers access to most basic attributes for metabolites, proteins, reactions, pathways and organisms in the database. The Python interface comes with an disk-based caching mechanism under
~/.biocyc that greatly reduces the delay (and load) for BioCyc servers.
The interface supports multiple + configurable caches, so it’s possible to share the cache across multiple machines.
biocyc module is hosted on PyPi and can be installed from the command line with:
pip install biocyc
Read on for more info.
biocyc object from the
biocyc module. This object provides the base access to the database for the initial get. You can set the organism using
set_organism and one of the standard BioCyc database identifiers. Note that this only affects the organism-database used for direct requests on the biocyc object. Sub-requests on existing objects will use the same database as that object (otherwise things would be very confusing indeed).
import os from biocyc import biocyc os.environ['http_proxy'] = '' # Set your proxy if neccessary biocyc.set_organism('meta')
Making a request¶
To get an database object (of any type) simply using the unique BioCyc identifiers for it. Here we request
L-Lactate. Note that if you do this from within an IP[y] Notebook you get a nice table output of all associated attributes for an object. This includes direct links to the BioCyc database and other database annotations.
|Reactions||TRANS-RXN-104, RXN-12165, RXN-12096, LACTALDDEHYDROG-RXN, RXN0-5269, D-LACTATE-2-SULFATASE-RXN, TRANS-RXN-104, L-LACTDEHYDROGFMN-RXN, LACTATE-MALATE-TRANSHYDROGENASE-RXN, LACTATE-2-MONOOXYGENASE-RXN, L-LACTATE-DEHYDROGENASE-CYTOCHROME-RXN, L-LACTATE-DEHYDROGENASE-RXN, RXN-9067, RXN-8076, PROPIONLACT-RXN, LACTATE-RACEMASE-RXN, LACTATE-ALDOLASE-RXN|
|Database links||CAS: 79-33-4, PUBCHEM: 5460161, LIGAND-CPD: C00186, CHEMSPIDER: 4573803, CHEBI: 16651, BIGG: 34179|
Now we have an object we can perform sub-queries by accessing fields. If you access the
o.reactions field you will trigger a dynamic request for all entities in that list. Connections to the BioCyc server are throttled at 1/second, so this may take a little while on long lists. However, retrieved data is cached under
~/.biocyc so subsequent requests will be much quicker. By default the cache is set to expire objects after ~6 months, and the cache folder can be shared between multiple machines.
_Note: If you just want access to the identifiers, you can use the
o._reactions field to access these without triggering a request_
r = o.reactions r
[TRANS-RXN-104, NADP<sup>+</sup> L-lactaldehyde dehydrogenase, L-2,4-diketo-3-deoxyrhamnoate hydrolase, LACTALDDEHYDROG-RXN, RXN0-5269, D-LACTATE-2-SULFATASE-RXN, TRANS-RXN-104, lactate oxidation, LACTATE-MALATE-TRANSHYDROGENASE-RXN, LACTATE-2-MONOOXYGENASE-RXN, L-LACTATE-DEHYDROGENASE-CYTOCHROME-RXN, L-LACTATE-DEHYDROGENASE-RXN, RXN-9067, RXN-8076, PROPIONLACT-RXN, LACTATE-RACEMASE-RXN, LACTATE-ALDOLASE-RXN]
You can access sub-entities and manipulate objects using standard Python list processing.
ps = [r.pathways for r in o.reactions] p = [p for sl in ps for p in sl] p
[L-rhamnose degradation II, L-rhamnose degradation III, L-rhamnose degradation II, methylglyoxal degradation V, lactate biosynthesis (archaea), L-lactaldehyde degradation (aerobic), L-lactaldehyde degradation (aerobic), methylglyoxal degradation V, pyruvate fermentation to lactate, glucose and xylose degradation, Bifidobacterium shunt, heterolactic fermentation, factor 420 biosynthesis]
|Name||L-rhamnose degradation II|
|Species||TAX-5580, ORG-6176, TAX-95486, TAX-284592, TAX-322104|
|Taxonomic range||TAX-2, TAX-4751|
That’s all for now! Hopefully this shows how Python (and IPython notebook) access to the BioCyc Web API may be useful. Support for additional attributes, API calls etc. is planned for the future. If you have specific requests, get in touch!
- Automatic phase correction of NMR spectra
- Pathomx: Analysis of public GEO datasets
- Pathomx: Example Analysis
- NMRLab 1D NMR processing (MATLAB)
- 1D 1H NMR data processing
Get my latest Python projects, tips & tutorials direct to your Inbox.