Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 177 tok/s
Gemini 2.5 Pro 43 tok/s Pro
GPT-5 Medium 26 tok/s Pro
GPT-5 High 25 tok/s Pro
GPT-4o 119 tok/s Pro
Kimi K2 202 tok/s Pro
GPT OSS 120B 439 tok/s Pro
Claude Sonnet 4.5 38 tok/s Pro
2000 character limit reached

A Review of Deep Learning Techniques for Protein Function Prediction (2211.09705v1)

Published 27 Oct 2022 in q-bio.BM, cs.AI, and cs.LG

Abstract: Deep Learning and big data have shown tremendous success in bioinformatics and computational biology in recent years; artificial intelligence methods have also significantly contributed in the task of protein function classification. This review paper analyzes the recent developments in approaches for the task of predicting protein function using deep learning. We explain the importance of determining the protein function and why automating the following task is crucial. Then, after reviewing the widely used deep learning techniques for this task, we continue our review and highlight the emergence of the modern State of The Art (SOTA) deep learning models which have achieved groundbreaking results in the field of computer vision, natural language processing and multi-modal learning in the last few years. We hope that this review will provide a broad view of the current role and advances of deep learning in biological sciences, especially in predicting protein function tasks and encourage new researchers to contribute to this area.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.