PhytoMine-I tried to get the genetic information of plants with Python

I found out that there is a PhytoMine that can call the data of Phytozome from Python, so I tried it. Phytozome is a site familiar to plant researchers, and is a convenient site for examining the genomic and genetic information of various plant species.

PhytoMine is one of the registries of a data warehouse system called InterMine.

InterMine is an open source data warehouse system licensed under LGPL2.1. InterMine is used to create a database of biological data accessed by advanced web query tools. You can use InterMine to create a database from a single dataset or integrate multiple data sources. Support for some common biological formats is provided and there is a framework for adding other data. InterMine includes a user-friendly web interface that works "out of the box" and is easy to customize. From Wikipedia "InterMine"

InterMine is available in a variety of programming languages, including Python. See API and Client Libraries for more information.

I tried using PhytoMine in Python by referring to InterMine-Python Tutorial. The installation was done with pip.

$ pip install intermine

I specified the gene function and plant species as a query and tried to get a list of genes in Python. The list was created in Pandas. The source code is as follows.

size = 20 #Specify the number of data to acquire

import pandas as pd
from intermine.webservice import Service

service = Service("https://phytozome.jgi.doe.gov/phytomine/service") #Create an instance by specifying the URL of PhytoMine
query = service.new_query("Gene") #Get genetic information
query.add_constraint("briefDescription","CONTAINS","transcription factor") #Specify gene function(Condition A)
query.add_constraint("name","CONTAINS","Eucgr") #At the beginning of the gene name of Eucalyptus Grandis"Eucgr"Designate Eucalyptus Grandis as a plant species using(Condition B)
query.add_constraint("name","CONTAINS","Potri") #At the beginning of the poplar gene name"Potri"Designate poplar as a plant species using(Condition C)
query.set_logic("A & (B | C)") #Settings for examining the genes of both Eucalyptus Grandis and Poplar(Condition A and condition B or condition C)

dfs = [] #Create an empty list to save the output
for row in query.rows(size=size):
    dfs.append(pd.DataFrame(row.values(),index=row.keys()).T) #Get data and save to list

dfs = pd.concat(dfs) #Convert list to dataframe
dfs.to_csv("Tree_TFs_Top20.csv")  #Save dataframe in csv format

Looking at PhytoMine's Query Builder page, it seems that there are various data types other than genes that can be used for queries, so I will try it little by little. I want to.