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How to build a Bioinformatics web app (Molecular Descriptor Calculator) in Python | Streamlit #21
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Streamlit (Web Application in Python) - How to build a Bioinformatics web app (Molecular Descriptor Calculator) in Python | Streamlit #21

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  • 13.5 hours of video
  • Certificate of completion
  • Access on mobile and TV

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In this video, I will be showing you how to build a molecular descriptor calculation web app in Python using the Streamlit library. Briefly, this molecular descriptor app is a Bioinformatics tool that will allow you to describe the unique molecular features of compounds in numerical form that can then be used to build predictive models using machine learning for predicting drug bioactivity, biological activities and chemical properties. Such models are also known as quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) models. Under the hood the bioinformatics tool that we will be building is based on using the PaDEL-Descriptor software for calculating molecular properties of compounds. 👉 Code: https://github.com/dataprofessor/moldesc-app 🌟 Subscribe to this YouTube channel https://www.youtube.com/dataprofessor?sub_confirmation=1 🌟 Join the Newsletter of Data Professor http://sendfox.com/dataprofessor 🌟 Buy me a coffee https://www.buymeacoffee.com/dataprofessor 🌟 Download Kite for FREE https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=dataprofessor&utm_content=description-only ⭕ Playlist: Check out our other videos in the following playlists. ✅ Data Science 101: https://bit.ly/dataprofessor-ds101 ✅ Data Science YouTuber Podcast: https://bit.ly/datascience-youtuber-podcast ✅ Data Science Virtual Internship: https://bit.ly/dataprofessor-internship ✅ Bioinformatics: http://bit.ly/dataprofessor-bioinformatics ✅ Data Science Toolbox: https://bit.ly/dataprofessor-datasciencetoolbox ✅ Streamlit (Web App in Python): https://bit.ly/dataprofessor-streamlit ✅ Shiny (Web App in R): https://bit.ly/dataprofessor-shiny ✅ Google Colab Tips and Tricks: https://bit.ly/dataprofessor-google-colab ✅ Pandas Tips and Tricks: https://bit.ly/dataprofessor-pandas ✅ Python Data Science Project: https://bit.ly/dataprofessor-python-ds ✅ R Data Science Project: https://bit.ly/dataprofessor-r-ds ✅ Weka (No Code Machine Learning): http://bit.ly/dp-weka ⭕ Recommended Books: 🌟https://kit.co/dataprofessor ✅ Hands-On Machine Learning with Scikit-Learn : https://amzn.to/3hTKuTt ✅ Data Science from Scratch : https://amzn.to/3fO0JiZ ✅ Python Data Science Handbook : https://amzn.to/37Tvf8n ✅ R for Data Science : https://amzn.to/2YCPcgW ✅ Artificial Intelligence: The Insights You Need from Harvard Business Review: https://amzn.to/33jTdcv ✅ AI Superpowers: China, Silicon Valley, and the New World Order: https://amzn.to/3nghGrd ⭕ Stock photos, graphics and videos used on this channel: ✅ https://1.envato.market/c/2346717/628379/4662 ⭕ Follow us: ✅ Medium: http://bit.ly/chanin-medium ✅ FaceBook: http://facebook.com/dataprofessor/ ✅ Website: http://dataprofessor.org/ (Under construction) ✅ Twitter: https://twitter.com/thedataprof/ ✅ Instagram: https://www.instagram.com/data.professor/ ✅ LinkedIn: https://www.linkedin.com/in/chanin-nantasenamat/ ✅ GitHub 1: https://github.com/dataprofessor/ ✅ GitHub 2: https://github.com/chaninlab/ ⭕ Disclaimer: Recommended books and tools are affiliate links that gives me a portion of sales at no cost to you, which will contribute to the improvement of this channel's contents. #streamlit #bioinformatics #drugdiscovery #machinelearning #python #bigdata #datascienceproject #randomforest #decisiontree #svm #neuralnet #neuralnetwork #supportvectormachine #learnpython #pythonprogramming #datascience #datamining #bigdata #datascienceworkshop #dataminingworkshop #dataminingtutorial #datasciencetutorial #ai #artificialintelligence #tutorial #dataanalytics #dataanalysis #machinelearningmodel #dataprofessor #artificialintelligence #ai #computationalbiology

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