Giter VIP home page Giter VIP logo

bioactivity-prediction-app's Introduction

bioactivity-prediction-app

Watch the tutorial video

Bioinformatics Project from Scratch - Drug Discovery #6 (Deploy Model as Web App) | Streamlit #22

Bioinformatics Project from Scratch - Drug Discovery #6 (Deploy Model as Web App) | Streamlit #22

Reproducing this web app

To recreate this web app on your own computer, do the following.

Create conda environment

Firstly, we will create a conda environment called bioactivity

conda create -n bioactivity python=3.7.9

Secondly, we will login to the bioactivity environement

conda activate bioactivity

Install prerequisite libraries

Download requirements.txt file

wget https://raw.githubusercontent.com/dataprofessor/bioactivity-prediction-app/main/requirements.txt

Pip install libraries

pip install -r requirements.txt

Download and unzip contents from GitHub repo

Download and unzip contents from https://github.com/dataprofessor/bioactivity-prediction-app/archive/main.zip

Generating the PKL file

The machine learning model used in this web app will firstly have to be generated by successfully running the included Jupyter notebook bioactivity_prediction_app.ipynb. Upon successfully running all code cells, a pickled model called acetylcholinesterase_model.pkl will be generated.

Launch the app

streamlit run app.py

bioactivity-prediction-app's People

Contributors

dataprofessor avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar

bioactivity-prediction-app's Issues

Doubts

Hello prof Chanin Nantasenamat,
first, let me say thanks for your videos. It's opening a part of my lab for Chemoinformatics in Rio (Brazil).

So, let me go for a question: I'm having a though time to run padelpy to get descriptors from a list of SMILES and structure Objects in a dataframe I have in Jupyter Notebook. Maybe I installed padelpy wrongly or my limitation in understanding this can also be the error I'm getting from using wget. I'm following this: https://github.com/ecrl/padelpy and https://analyticsindiamag.com/hands-on-guide-to-padelpy-for-ml-model-building/, but I think I need extensions that I don't know of..
Any tips?

Thank you
Ricardo Borges

error in ubuntu 20

git clone https://github.com/dataprofessor/bioactivity-prediction-app.git
cd bioactivity-prediction-app
wget https://raw.githubusercontent.com/dataprofessor/moldesc-app/main/requirements.txt
pip install -r requirements.txt

show this

root@two-ubuntu-s-8vcpu-16gb-nyc1-01:~/bioactivity-prediction-app# pip install -r requirements.txt
Collecting streamlit==0.71.0
  Downloading streamlit-0.71.0-py2.py3-none-any.whl (7.4 MB)
     |████████████████████████████████| 7.4 MB 27.4 MB/s
Collecting pandas==1.1.3
  Downloading pandas-1.1.3-cp38-cp38-manylinux1_x86_64.whl (9.3 MB)
     |████████████████████████████████| 9.3 MB 38.3 MB/s
Collecting base58==2.0.1
  Downloading base58-2.0.1-py3-none-any.whl (4.3 kB)
ERROR: Could not find a version that satisfies the requirement subprocess (from -r requirements.txt (line 4)) (from versions: none)
ERROR: No matching distribution found for subprocess (from -r requirements.txt (line 4))

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.