chapmanb

from systemsbio import *
server = Biogateway()

results = server.search("Homo sapiens",
        [RetrieveProtein(), RetrieveInteractor()],
        [SelectByGOTerm('insulin'), SelectByDisease('diabetes')])
print results.dtype.names
result = results[0]
print result['protein'], result['interactor'], result['GO_term']

chapmanb

from intermine import Intermine, ExperimentQueryBuilder
builder = ExperimentQueryBuilder()
builder.add_attributes(["submission_id", "experiment_name"])
builder.add_filter("organism", "Caenorhabditis elegans")
builder.free_text_filter("ChIP-seq")
    
server = Intermine("http://intermine.modencode.org")
table = server.search(builder)
print table.dtype.names
print table

chapmanb

from systemsbio import Biogateway, UniProtGOQueryBuilder

builder = UniProtGOQueryBuilder("Homo sapiens")
builder.add_filter("GO_term", "insulin")
builder.add_filter("disease_description", "diabetes")
builder.add_attributes(["protein_name", "interactor", "gene_name"])
        
server = Biogateway()
results = server.search(builder)
print len(results), results.dtype.names

chapmanb

from systemsbio import Biogateway, ReferenceBuilder

builder = ReferenceBuilder()
builder.add_filter("protein_id", "1433B_HUMAN")
builder.add_attributes(["reference"])

server = Biogateway()
results = server.search(builder)
print len(results), results.dtype.names
result = results[0]

chapmanb

from Bio import Entrez
Entrez.email = "me@example.com"
pubmed_id = result['reference'].replace("PMID_", "")
handle = Entrez.esummary(db="pubmed", id=pubmed_id)
record = Entrez.read(handle)[0]
print record['Title']
print record['PubDate']
print ",".join(record['AuthorList'])
print record['FullJournalName'], record['Volume'], record['Pages']
# Novel raf kinase protein-protein interactions found by an exhaustive yeast two-hybrid analysis.

chapmanb

from intermine import Intermine, SubmissionQueryBuilder
builder = SubmissionQueryBuilder()
builder.add_attributes(["submission_id", 
    "submission_title", "developmental_stage"])
builder.add_filter("organism", "Caenorhabditis elegans")
builder.add_filter("antibody_name", "H3K4me3")

server = Intermine("http://intermine.modencode.org")
table = server.search(builder)
print table.dtype.names

chapmanb

import os
import subprocess
import tempfile

from Bio import SeqIO
from Bio.Emboss.Applications import NeedleCommandline

# read in file from somewhere
in_file = os.path.join("Tests", "NeuralNetwork", "enolase.fasta")
in_handle = open(in_file)

chapmanb

>1
*
>2
MKFTGTPATNEILLQKVGGVCVEMNPCWARRKFSVCVLFGFLIMADVSTSLCPWSPATGV
RWSSGGFVLYFICCFFFIFQCLYLLLLIIHICLFYLLLLSSVIYCCSLLILFSVIYFTII
MN*
>3
MRTLFPDHPHLLPGGDVMSTCEGERERERKPDLVCVVLACNCFVFRVLFAPKPEKSQDSV
SETQLPQL*
>4

chapmanb

>Contig5.15.path1.gene1
*
>Contig5.15.path1.gene2
MKFTGTPATNEILLQKVGGVCVEMNPCWARRKFSVCVLFGFLIMADVSTSLCPWSPATGV
RWSSGGFVLYFICCFFFIFQCLYLLLLIIHICLFYLLLLSSVIYCCSLLILFSVIYFTII
MN*
>Contig5.15.path1.gene3
MRTLFPDHPHLLPGGDVMSTCEGERERERKPDLVCVVLACNCFVFRVLFAPKPEKSQDSV
SETQLPQL*
>Contig5.15.path1.gene4

chapmanb

Developing an open source community for cloud bioinformatics

- Main points
  = Developing open source code in biology especially difficult.
  = Most productive target for work is developer resources.
  = Community emerging to develop and maintain images.

- Open source background:
  = OpenBio, Bio* projects, Biopython
  = Grad school -- developed distributed system with BSP. Never reused: why