Ricardo Avila ravila4

## parse_drugbank_xml.py
import xmltodict
import pandas as pd

with open("full_database.xml") as db:
    doc = xmltodict.parse(db.read())

values = []
for item in doc['drugbank']['drug']:
    logp = None
    try:

## align.py
#!/usr/bin/env python

# Sequence alignment using PyMOL
# The purpose of this script is to generate a sequence alignment between
# the original crystal structure of the apo and holo models, and the sequence
# of the finalised, ungapped Rosetta models. This allows us to get a 1 to 1
# corresponcence between the residue numberings in both structures.

# USAGE: Run once from the project root.
# "pockets.csv" contains the information about apo holo pairs.

## HTS_gaussian.ipynb

      
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                ravila4
                / HTS_gaussian.ipynb
            
            
              Created
              October 24, 2019 20:38
            
              
                Fitting Gaussian curves to histograms
              
          
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## flatten_json.py
def flatten_json(y):
    out = {}

    def flatten(x, name=''):
        if type(x) is dict:
            for a in x:
                flatten(x[a], name + a + '_')
        elif type(x) is list:
            i = 0
            for a in x:

## parallel.py
# Functions for parallelizing things

def init_spark(nproc=-1, appname="sparksession"):
    """Function to start a Spark executor."""
    from pyspark.sql import SparkSession
    if nproc == -1:
        # Use all CUPs
        spark = SparkSession.builder.master(
                "local[*]").appName(appname).getOrCreate()
    else:

## pandas_snippets.py
# List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

# Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

# Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(valuelist)]

## csv_to_fasta.py
#!/usr/bin/env python

import pandas as pd
import click
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
from Bio import SeqIO


@click.command()

## make_blast_db.sh
#!/bin/bash
TYPE=${TYPE:-prot}
[[ ! -z ${1} ]] && INFILE=${1} || exit 1
shift
makeblastdb -in ${INFILE} -dbtype ${TYPE} -parse_seqids ${@} -blastdb_version 5

## runblast.sh
blastp -db fasta.fa -query database.fa \
    -outfmt "6 std stitle qcovs" -num_threads 10 -out out.blast

## .tmux.conf
# $Id: vim-keys.conf,v 1.2 2010-09-18 09:36:15 nicm Exp $
#
# vim-keys.conf, v1.2 2010/09/12
#
# By Daniel Thau.  Public domain.
#
# This configuration file binds many vi- and vim-like bindings to the
# appropriate tmux key bindings.  Note that for many key bindings there is no
# tmux analogue.  This is intended for tmux 1.3, which handles pane selection
# differently from the previous versions
	import xmltodict
	import pandas as pd

	with open("full_database.xml") as db:
	doc = xmltodict.parse(db.read())

	values = []
	for item in doc['drugbank']['drug']:
	logp = None
	try:
	#!/usr/bin/env python

	# Sequence alignment using PyMOL
	# The purpose of this script is to generate a sequence alignment between
	# the original crystal structure of the apo and holo models, and the sequence
	# of the finalised, ungapped Rosetta models. This allows us to get a 1 to 1
	# corresponcence between the residue numberings in both structures.

	# USAGE: Run once from the project root.
	# "pockets.csv" contains the information about apo holo pairs.
	def flatten_json(y):
	out = {}

	def flatten(x, name=''):
	if type(x) is dict:
	for a in x:
	flatten(x[a], name + a + '_')
	elif type(x) is list:
	i = 0
	for a in x:
	# Functions for parallelizing things

	def init_spark(nproc=-1, appname="sparksession"):
	"""Function to start a Spark executor."""
	from pyspark.sql import SparkSession
	if nproc == -1:
	# Use all CUPs
	spark = SparkSession.builder.master(
	"local[*]").appName(appname).getOrCreate()
	else:
	# List unique values in a DataFrame column
	pd.unique(df.column_name.ravel())

	# Convert Series datatype to numeric, getting rid of any non-numeric values
	df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

	# Grab DataFrame rows where column has certain values
	valuelist = ['value1', 'value2', 'value3']
	df = df[df.column.isin(valuelist)]
	#!/usr/bin/env python

	import pandas as pd
	import click
	from Bio.Seq import Seq
	from Bio.SeqRecord import SeqRecord
	from Bio import SeqIO


	@click.command()
	#!/bin/bash
	TYPE=${TYPE:-prot}
	[[ ! -z ${1} ]] && INFILE=${1} \|\| exit 1
	shift
	makeblastdb -in ${INFILE} -dbtype ${TYPE} -parse_seqids ${@} -blastdb_version 5
	blastp -db fasta.fa -query database.fa \
	-outfmt "6 std stitle qcovs" -num_threads 10 -out out.blast
	# $Id: vim-keys.conf,v 1.2 2010-09-18 09:36:15 nicm Exp $
	#
	# vim-keys.conf, v1.2 2010/09/12
	#
	# By Daniel Thau. Public domain.
	#
	# This configuration file binds many vi- and vim-like bindings to the
	# appropriate tmux key bindings. Note that for many key bindings there is no
	# tmux analogue. This is intended for tmux 1.3, which handles pane selection
	# differently from the previous versions