The heavy metal pollution in arable soil poses a significant threat to human health. Thus, it is
of great significance to investigate the contamination of heavy metal elements in the soil. As …

The ever-decreasing cost of sequencing and the growing potential applications of
metagenomics have led to an unprecedented surge in data generation. One of the most …

Microbial and microbiome data consist of large data matrices that contain many irrelevant or
colinear features. This can hinder the performance of machine learning algorithms because …

Heavy metal pollution not only causes detrimental effects on the environment but also poses
threats to human health; thus, it is crucial to monitor the heavy metal content in the soil …

The community of microbes including bacteria, viruses, fungi etc. living in and on our body is
known as the human microbiome. The human microbiome plays an important role in life …

In a generic computational environment for biological data processing, classifying DNA
sequences is an important task. In recent times, a range of machine learning methods have …

Medicine and biology are important research fields with a significant impact on humans and
their health. In the last few decades, many visualization strategies have been proposed for …

Variational inference algorithms seek to estimate the posterior of latent variables using
anapproximate inference model. Within this, Variational Auto-Encoders (VAEs) provide an …

The composition and function of the human gut microbiome are associated with many
aspects of human health and disease and are shaped by diet. Staple grains, which comprise …

Sequencing in metagenomes opens new ways of analyzing genomics in microbial
communities in their habitats. Analyzing metagenomes has been a challenge not only …