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MetaLocGramN 0.99

MetaLocGramN: a method for subcellular localization prediction of Gram-negative proteins.

Welcome to MetaLocGramN
---------------

The MetaLocGramN is a method for subcellular localization prediction of Gram-negative proteins.
Read more: http://iimcb.genesilico.pl/MetaLocGramN/home

How does MetaLocGramN work?
============

The MetaLocGramN is a gateway to a number of primary prediction methods (various types: signal peptide, beta-barrel, transmembrane helices and subcellular localization predictors).

The MetaLocGramN integrates the primary methods and based on their outputs provides overall consensus prediction.

Requirements
============

* suds = 0.4

Installation
============

Install it with pip (or easy_install)::

        pip install MetaLocGramN

How to start?
============

If you are really lazy try:

        $ ipython

        In [1]: from MetaLocGramN import *
        In [2]: run_example()
        # job_id: 1X820N
        # status: queue
        # status: primary prediction::in progress
        # status: primary prediction::in progress
        # status: primary prediction::done
        # status: consenus::done
        # status: done
        extracellular,47.541,0.0,0.0,0.0,52.459,
        primary methods: CELLO,cytoplasmic,0.6138,0.036,0.1346,0.0612,0.1546,PSLpred,extracellular,0.2,0.531,PSORTb3,unknown,0.2,0.2,0.2,0.2,0.2,SosuiGramN,cytoplasmic
        In [3]: run_example?
        # to get help!
        In [4]: run_example??
        # to get even bigger help!

if you want to find out more, see test.py inside the pkg.

        import MetaLocGramN
        import time

        if __name__ == "__main__":
            mlgn = MetaLocGramN.MLGN()

            seq = """>fasta
            MKLSINKNTLESAVILCNAYVEKKDSSTITSHLFFHADEDKLLIKASDYEIGI
            NYKIKKIRVESSGFATANAKSIADVIKSLNNEEVVLETIDNFLFVRQKNTKYK
            """
            mlgn.predict(seq)
            print '# job_id:', mlgn.get_job_id()
            status = ''
            while True:
                status = mlgn.get_status()
                print '# status:', status
                if status == 'done':
                    break
                time.sleep(5)
            print mlgn.get_result()

You should get something like:

        python test.py
        # job_id: K6Q10Q
        # status: queue
        # status: queue
        # status: primary prediction::in progress
        # status: primary prediction::in progress
        # status: primary prediction::done
        # status: done
        extracellular,47.541,0.0,0.0,0.0,52.459,
        primary methods: CELLO,cytoplasmic,0.6138,0.036,0.1346,0.0612,0.1546,PSLpred,extracellular,0.2,0.531,PSORTb3,unknown,0.2,0.2,0.2,0.2,0.2,SosuiGramN,cytoplasmic

Authors
==================================================

Marcin Magnus,
Marcin Pawlowski,
Janusz M. Bujnicki

http://iimcb.genesilico.pl/


Happy predictions!
==================================================

Marcin Magnus magnus@genesilico.pl
 
File Type Py Version Uploaded on Size
MetaLocGramN-0.99.tar.gz (md5) Source 2012-10-01 14KB
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