Abstract Artificial intelligence employs Machine Learning (ML) and Deep Learning (DL) to
analyze data. In both, the data is stored centrally. The data involved may be sensitive and …

The efficient analysis and interpretation of biological sequence data remain major
challenges in bioinformatics. Graphical representation, as an emerging and effective …

In the context of graduate learning in China, mentors are the teachers with the highest
frequency of contact and the closest relationships with postgraduate students. Nevertheless …

When Nitrogen Dioxide (NO2) and Sulfur Dioxide (SO2) mix, they cause pulmonary fibrosis,
and severe public health issues. Therefore, introducing deep learning models to predict …

Multilevel inverters (MLI) perform a significant role in microgrids to overcome the power
demand for various load conditions due to violations of load day by day in recent centuries …

Understanding the differences between genomic sequences of different lives is crucial for
biological classification and phylogeny. Here, we downloaded all the reliable sequences of …

Background: This study addresses the need for analyzing viral genome sequences and
understanding their genetic relationships. The focus is on introducing a novel natural graph …

Biological sequence analysis is the most fundamental work in bioinformatics. Many research
methods have been developed in the development of biological sequence analysis. These …

In this work, we utilized resting-state functional connectivity (FC) data to construct diagnostic
classifiers using machine learning classifiers like random forest algorithms on four different …

Analytics and filtering are becoming more and more important in the online retail space to
improve consumer experience and guide corporate strategy. The abundance of faked …