API - Documentation
epitope1D is also available through an API (Application Programming Interface), which can be a usefull tool for other research applications aiming to access our prediction resources.
The submission is processed by our server in a queue and receive an unique identifier called Job ID. Using this ID you will be able to check the status and receive the result when ready.
Here we present how to use it:
Job Submission (POST) https://biosig.lab.uq.edu.au/epitope1d/api/submission
Arguments
- fasta (required) - Fasta file containing header '>' and sequences.
- organism (required) - Organism Taxonomy Nomeclature. Choose only 1: Metamonada, Discoba, Sar, Viridiplantae, Opisthokonta, Terrabacteria group, Proteobacteria, PVC group, Spirochaetes, FCB group, Thermodesulfobacteria, Fusobacteria, Riboviria, Duplodnaviria, Monodnaviria, Varidnaviria, Ribozyviria, Anelloviridae, Naldaviricetes, Adnaviria.
- window (required) - If your file contains full protein sequences, please inform the window size to screen for linear epitopes. The value should be and integer in between 6 and 25. (Recommended value is 25)
- email (optional) - Email for contact when the job is finished or if an error occurs.
Return
- job_id - ID used for uniquely identify each job
Examples
-
curl
$ curl https://biosig.lab.uq.edu.au/epitope1d/api/submission -X POST -i -F fasta=myfastafile.fasta \ -F organism=Riboviria -F window=25 -F email=xxxx@gmail.com
{ "job_id": "161954773493" }
Retrieve Job Results (GET) https://biosig.lab.uq.edu.au/epitope1d/api/submission
Arguments
- job_id - ID used for uniquely identify each job. Generated upon submission
Return
For jobs still being processed or waiting on queue, the message below will be returned from querying this endpoint:- message - running
- prediction -
Examples
-
curl
$ curl https://biosig.lab.uq.edu.au/epitope1d/api/submission -X GET -F job_id=161954773493
{ "fasta_header_1": { "Peptide": "EGKLLFVPLNLS", "prediction": "non-epitope", "score": 0.24 }, "fasta_header_2": { "Peptide": "PPETNDFYFQQTMLR", "prediction": "epitope", "score": 0.617 }