Deep learning in bioinformatics: introduction, application, and perspective in big data era

02/28/2019
by   Yu Li, et al.
0

Deep learning, which is especially formidable in handling big data, has achieved great success in various fields, including bioinformatics. With the advances of the big data era in biology, it is foreseeable that deep learning will become increasingly important in the field and will be incorporated in vast majorities of analysis pipelines. In this review, we provide both the exoteric introduction of deep learning, and concrete examples and implementations of its representative applications in bioinformatics. We start from the recent achievements of deep learning in the bioinformatics field, pointing out the problems which are suitable to use deep learning. After that, we introduce deep learning in an easy-to-understand fashion, from shallow neural networks to legendary convolutional neural networks, legendary recurrent neural networks, graph neural networks, generative adversarial networks, variational autoencoder, and the most recent state-of-the-art architectures. After that, we provide eight examples, covering five bioinformatics research directions and all the four kinds of data type, with the implementation written in Tensorflow and Keras. Finally, we discuss the common issues, such as overfitting and interpretability, that users will encounter when adopting deep learning methods and provide corresponding suggestions. The implementations are freely available at <https://github.com/lykaust15/Deep_learning_examples>.

READ FULL TEXT
research
03/23/2023

Reimagining Application User Interface (UI) Design using Deep Learning Methods: Challenges and Opportunities

In this paper, we present a review of the recent work in deep learning m...
research
02/02/2022

Deep Learning for Epidemiologists: An Introduction to Neural Networks

Deep learning methods are increasingly being applied to problems in medi...
research
02/08/2021

Introduction to Machine Learning for the Sciences

This is an introductory machine learning course specifically developed w...
research
08/23/2022

Latent Variable Models in the Era of Industrial Big Data: Extension and Beyond

A rich supply of data and innovative algorithms have made data-driven mo...
research
05/31/2022

Graph-level Neural Networks: Current Progress and Future Directions

Graph-structured data consisting of objects (i.e., nodes) and relationsh...
research
03/29/2022

Graph Neural Networks in IoT: A Survey

The Internet of Things (IoT) boom has revolutionized almost every corner...
research
11/18/2019

Hacking Neural Networks: A Short Introduction

A large chunk of research on the security issues of neural networks is f...

Please sign up or login with your details

Forgot password? Click here to reset