In the era of big data, transformation of biomedical big data into valuable knowledge has
been one of the most important challenges in bioinformatics. Deep learning has advanced …

Rapid advances in biological research over recent years have significantly enriched
biological and medical data resources. Deep learning-based techniques have been …

The fields of medicine science and health informatics have made great progress recently
and have led to in-depth analytics that is demanded by generation, collection and …

Extracting inherent valuable knowledge from omics big data remains as a daunting problem
in bioinformatics and computational biology. Deep learning, as an emerging branch from …

Deep learning is a subfield of machine learning that considers computational models with
multiple processing layers [1, 3, 6]. At the core of all deep learning approaches lies …

With the progress of medical technology, biomedical field ushered in the era of big data,
based on which and driven by artificial intelligence technology, computational medicine has …

Gaining knowledge and actionable insights from complex, high-dimensional and
heterogeneous biomedical data remains a key challenge in transforming health care …

With the evolution of biotechnology and the introduction of the high throughput sequencing,
researchers have the ability to produce and analyze vast amounts of genomics data. Since …

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 …

In recent years, deep learning has been widely used in diverse fields of research, such as
speech recognition, image classification, autonomous driving and natural language …