生物信息学中的深度神经网络应用

计算机工程与设计 Pub Date : 2022-09-23 DOI:10.1109/SEEDA-CECNSM57760.2022.9932895

D. Amanatidis, K. Vaitsi, Michael F. Dossis

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引用次数: 1

摘要

由于深度学习和生物信息学是不断发展的领域，本文重点介绍了四种类型的深度神经网络;前馈、循环、卷积和生成对抗网络及其在生物信息学七个重要领域的最新应用系统生物学，序列分析，结构预测与表征，生物分子特性与功能预测，生物医学图像处理与诊断，生物分子相互作用预测，蛋白质工程。这两层的层次结构在整个论文中都保留了下来，从而实现了清晰和全面的展示。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Deep Neural Network Applications for Bioinformatics

As Deep Learning and Bioinformatics are constantly evolving fields, this review focuses on four types of Deep Neural Networks; Feedforward, Recurrent, Convolutional and Generative Adversarial Networks and their respective latest applications in seven important fields of Bioinformatics; Systems Biology, Sequence Analysis, Structure Prediction and Representation, Biomolecular Property and Function Prediction, Biomedical Image Processing and Diagnosis, Biomolecular Interaction Prediction and Protein Engineering. This two-level hierarchy is retained throughout the paper, enabling a clear and comprehensive presentation.

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来源期刊

计算机工程与设计

自引率

0.00%

发文量

20353

期刊介绍： Computer Engineering and Design is supervised by China Aerospace Science and Industry Corporation and sponsored by the 706th Institute of the Second Academy of China Aerospace Science and Industry Corporation. It was founded in 1980. The purpose of the journal is to disseminate new technologies and promote academic exchanges. Since its inception, it has adhered to the principle of combining depth and breadth, theory and application, and focused on reporting cutting-edge and hot computer technologies. The journal accepts academic papers with innovative and independent academic insights, including papers on fund projects, award-winning research papers, outstanding papers at academic conferences, doctoral and master's theses, etc.