Energy Minimization vs. Deep Learning Approaches for Protein Structure Prediction

被引：2

作者：

Luis Filgueiras, Juan ^{[1
]}

Varela, Daniel ^{[1
]}

Santos, Jose ^{[1
]}

机构：

[1] Univ A Coruna, CITIC Ctr Informat & Commun Technol Res, Dept Comp Sci & Informat Technol, La Coruna, Spain

来源：

BIO-INSPIRED SYSTEMS AND APPLICATIONS: FROM ROBOTICS TO AMBIENT INTELLIGENCE, PT II | 2022年 / 13259卷

关键词：

D O I：

10.1007/978-3-031-06527-9_11

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This article discusses the advantages and problems of different approaches to ab initio protein structure prediction. Recent successful approaches based on deep learning are compared with those based on protein fragment replacements and energy minimization with different search strategies, including ours based on evolutionary algorithms. Selected proteins are considered to analyze the approaches, focusing on the problems of those based on deep learning.

引用

页码：109 / 118

页数：10

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