Recent high throughput experimental methods have been used to collect large biomedical
omics datasets. Clustering of single omic datasets has proven invaluable for biological and …

Driven by high-throughput sequencing techniques, modern genomic and clinical studies are
in a strong need of integrative machine learning models for better use of vast volumes of …

Correlation and association analyses are one of the most widely used statistical methods in
research fields, including microbiome and integrative multiomics studies. Correlation and …

Data analysis is a very challenging task in LC-MS metabolomic studies. The use of powerful
analytical techniques (eg, high-resolution mass spectrometry) provides high-dimensional …

Foxtail millet (Setaria italica), which was domesticated from the wild species green foxtail
(Setaria viridis), is a rich source of phytonutrients for humans. To evaluate how breeding …

Medicinal plants are a rich source of highly diverse specialized metabolites with important
pharmacological properties. Until recently, plant biologists were limited in their ability to …

Covering: up to 2022 With the emergence of large amounts of omics data, computational
approaches for the identification of plant natural product biosynthetic pathways and their …

Computational integrative analysis has become a significant approach in the data-driven
exploration of biological problems. Many integration methods for cancer subtyping have …

Beverage quality in the brewing industry is heavily influenced by ingredient properties. The
contribution of raw ingredients such as yeast and hops to beer flavor is well understood …

Medicinal plants produce important substrates for their adaptation and defenses against
environmental factors and, at the same time, are used for traditional medicine and industrial …