"Predicting Protein Structure with Meta AI Practical Guide

[oaxino]

Published 8/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 44m | Size: 1.04 GB

"Learn practical protein structure Prediction without requiring heavy computational resources"

What you'll learn
Understand the basics of protein structures Levels of structure (primary, secondary, tertiary, quaternary) Why structure is critical for function and drug de
Explore the fundamentals of AI in protein structure prediction Overview of AI tools like Meta AI's ESMFold and how they compare with AlphaFold How AI is tran
Set up and use Meta AI's ESMFold for protein structure forecasting Installing and using necessary tools without heavy computing resources Using Google Colab f
Fetch protein sequences and predict their structures Using UniProt and other databases to find proteins of interest Submitting sequences for prediction and re
Requirements
Basic knowledge of biology
Understanding of protein structure levels (primary, secondary, tertiary) is helpful.
A willingness to learn and take action.
Description
Unlock the power of AI-driven bioinformatics by mastering Predicting Protein Structure using Meta AI! This comprehensive, beginner-friendly course will teach you how to predict, analyze, and visualize protein structures using Meta AI's ESMFold without requiring expensive lab equipment or heavy computational resources.Protein structure plays a critical role in understanding biological functions, designing drugs, and advancing research in biotechnology and healthcare. Traditional methods like X-ray crystallography and NMR are time-consuming and costly. With AI breakthroughs from Meta AI, you can now predict protein structures quickly and accurately to accelerate your research and project workflows.In this course, you will start with the fundamentals of protein structure, learning about primary, secondary, tertiary, and quaternary structures and why they are important in biology and drug design. You will then dive into the exciting world of AI-based protein structure prediction, understanding how tools like Meta AI's ESMFold are revolutionizing structural biology.Through hands-on tutorials using Google Colab, you will learn how to:Fetch protein sequences from databases like UniProt,Predict their structures using ESMFold,Visualize and interpret these structures using tools like PyMOL, Chimera, and Mol*.You will work on practical mini-projects, such as predicting the structure of a disease-related protein and comparing predicted structures with experimental data, gaining insights into drug discovery and protein engineering applications.This course also covers the limitations of AI in structure prediction, best practices, and ethical considerations, equipping you to apply these skills responsibly in your research or professional projects.Whether you are a student, researcher, bioinformatics enthusiast, or a professional in biotech or pharma, this course will empower you with practical, job-ready skills in AI-driven protein forecasting.By the end of this course, you will confidently predict and analyze protein structures, understand their implications in real-world scenarios, and add cutting-edge AI bioinformatics skills to your toolkit to stay ahead in your academic or professional journey.
Who this course is for
Biology and Biotechnology Students who want to learn how AI can help predict protein structures to support research and projects.
Bioinformatics Learners looking to add practical protein structure prediction skills to their toolkit without expensive lab work.
Researchers and PhD Scholars in life sciences aiming to accelerate their work by using AI-based structure prediction instead of waiting for experimental data.
Data Scientists & AI Enthusiasts interested in real-world applications of AI in biotech and healthcare.
ndustry Professionals in Pharma & Biotech who want to understand and apply AI-driven protein modeling in drug discovery workflows.
Educators and Trainers in Bioinformatics looking to understand ESMFold/Meta AI tools for integrating into their teaching.
Curious Learners interested in AI applications, drug design, and cutting-edge bioinformatics.
Homepage:

https://www.udemy.com/course/predicting-protein-structure-with-meta-ai-practical-guide/

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