Transposable elements (TEs) are genomic units able to move within the genome of virtually
all organisms. Due to their natural repetitive numbers and their high structural diversity, the …

The identification of regions of DNA sequences that code for proteins is one of the most
fundamental applications in bioinformatics. These protein-coding regions are in contrast to …

Data-driven machine learning, especially deep learning technology, is becoming an
important tool for handling big data issues in bioinformatics. In machine learning, DNA …

Because of the promising results obtained by machine learning (ML) approaches in several
fields, every day is more common, the utilization of ML to solve problems in bioinformatics. In …

This paper reports an experimental comparison of artificial neural network (ANN) and
support vector machine (SVM) ensembles and their “nonensemble” variants for lung cancer …

Due to the continued evolution of the SARS-CoV-2 pandemic, researchers worldwide are
working to mitigate, suppress its spread, and better understand it by deploying digital signal …

Motivation: DNA sequences can be represented by sequences of four symbols, but it is often
useful to convert the symbols into real or complex numbers for further analysis. Several …

Every day more plant genomes are available in public databases and additional massive
sequencing projects (ie, that aim to sequence thousands of individuals) are formulated and …

Numerous techniques are used to compare protein sequences based on the values of the
physiochemical properties of amino acids. In this work, a single physical/chemical property …

Genomic signal processing (GSP) refers to the use of signal processing for the analysis of
genomic data. GSP methods require the transformation or map** of the genomic data to a …