Google Researchers Use Machine Learning Approach To Annotate Protein Domains

Google Researchers Use Machine Learning Approach To Annotate Protein Domains

Google researchers have developed a machine learning approach to automatically annotate protein domains. Their solution is a deep learning architecture that identifies the protein domains from the amino acid sequence of the target protein.

Protein domains are important components of proteins, and they often determine how the protein behaves and is used in biological systems. Being able to accurately annotate protein domains is essential for understanding protein structure and function.

The Google team used a convolutional neural network, which is a type of deep learning algorithm, to predict protein domains from the amino acid sequence. The algorithm was trained using protein data from public databases, and it achieved an accuracy of over 84%.

This research provides a step forward in our ability to understand and use proteins. By providing accurate and automated annotations of protein domains, researchers can better understand how proteins work and develop new treatments and therapies for diseases.