Machine learning, a collection of data-analytical techniques aimed at building predictive
models from multi-dimensional datasets, is becoming integral to modern biological research …

The ability to efficiently adapt metabolism by substrate sensing, trafficking, storage, and
utilization, dependent on availability and requirement, is known as metabolic flexibility. In …

Endothelial cells (ECs) are more than inert blood vessel lining material. Instead, they are
active players in the formation of new blood vessels (angiogenesis) both in health and (life …

Abstract The Biomarkers of Nutrition for Development (BOND) project is designed to provide
evidence-based advice to anyone with an interest in the role of nutrition in health …

Multiple models of human metabolism have been reconstructed, but each represents only a
subset of our knowledge. Here we describe Recon 2, a community-driven, consensus' …

Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis
and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly …

Metabologenomics integrates metabolomics with other omics data types to comprehensively
study the genetic and environmental factors that influence metabolism. These multi-omics …

Motivation: The accurate identification of chemicals in text is important for many applications,
including computer-assisted reconstruction of metabolic networks or retrieval of information …

Background Human tissues perform diverse metabolic functions. Map** out these tissue-
specific functions in genome-scale models will advance our understanding of the metabolic …

Biological networks can be used to functionally annotate genes on the basis of interaction-
profile similarities. Metrics known as association indices can be used to quantify interaction …