The deep learning arena explores new dimensions once considered impossible to human
intelligence. Recently, it has taken footsteps in the biological data world to deal with the …

Artificial intelligence tools are gaining more and more ground each year in bioinformatics.
Learning algorithms can be taught for specific tasks by using the existing enormous …

Convolutional neural networks (CNNs) have been shown to perform exceptionally well in a
variety of tasks, including biological sequence classification. Available implementations …

Deep learning has proven to be a powerful method with applications in various fields
including image, language, and biomedical data. Thanks to the libraries and toolkits such as …

Classifying protein sequences from biological data has lot of importance in the field of
pharmacology. The application of machine learning to find the sequence of amino acids has …

Abstract Next Generation Sequencing (NGS) or deep sequencing technology enables
parallel reading of multiple individual DNA fragments, thereby enabling the identification of …

Biomacromolecules, primarily proteins, DNA, and RNA, are crucial for vital physiological
processes. Biomacromolecules can generally be represented by sequences, comprising …

DNA sequences are the basic data type that is processed to perform a generic study of
biological data analysis. One key component of the biological analysis is represented by …

Background: For decades, the rate of solving new biomolecular structures has been
exceeding that at which their manual classification and feature characterisation can be …

Here, we present DeepBIO, the first-of-its-kind automated and interpretable deep-learning
platform for high-throughput biological sequence functional analysis. DeepBIO is a one-stop …