Project Description for drug-repurposing-extract

This is a Python package for drug repurposing data extraction. You can use it to retrieve and analyze data related to specific compound IDs (CIDs) for potential drug repurposing.

Installation

You can install the package using pip:

pip install drug-repurposing-extract

Usage

Import the package

import drug_repurposing
from drug_repurposing import get_data

Generate CSV File from CID List

To generate a CSV file from a list of CIDs (Compound IDs), you can use the generate_data_from_list function:

get_data.generate_data_from_list([942, 1070])

Generate CSV List from Uploading a CSV File of CID List

You can also generate a CSV file from a list of CIDs by uploading a CSV file containing the CID list. Here's how you can do it in a Google Colab environment:

from google.colab import files
import io
import pandas as pd

uploaded = files.upload()
uploaded_file = list(uploaded.values())[0]
df = pd.read_csv(io.BytesIO(uploaded_file))
data = df["cid"].values

get_data.generate_data_from_list(data)

Predicting the CIDs Data

To predict data based on CIDs, you can follow these steps:

Make sure you have a CSV file (e.g., complete_data.csv) generated from the previous steps.

Read the CSV file using pandas:

import pandas as pd
df = pd.read_csv("complete_data.csv")

Use the predict_data function to perform predictions:

get_data.predict_data(df)