Biological networks have been widely used in many different diseases to identify potential
biomarkers and design drug targets. In the present review, we describe the main …

Network Medicine applies network science approaches to investigate disease
pathogenesis. Many different analytical methods have been used to infer relevant molecular …

Background Biological networks are important for elucidating disease etiology due to their
ability to model complex high dimensional data and biological systems. Proteomics provides …

The conventional reductionist approach to cardiovascular research investigates individual
candidate factors or linear signalling pathways but ignores more complex interactions in …

Abstraction of intracellular biomolecular interactions into networks is useful for data
integration and graph analysis. Network analysis tools facilitate predictions of novel …

Together with computational analysis and modeling, the development of whole-genome
measurement technologies holds the potential to fundamentally change research on …

Proteomics provides important information‐that may not be inferable from indirect sources
such as RNA or DNA‐on key players in biological systems or disease states. However, it …

Omics techniques generate large, multidimensional data that are amenable to analysis by
new informatics approaches alongside conventional statistical methods. Systems theories …

Network medicine can advance current medical practice by arising as response to the
limitations of a reductionist approach focusing on cardiovascular (CV) diseases as a direct …

Studying biological networks, such as protein-protein interactions, is key to understanding
complex biological activities. Various types of large-scale biological datasets have been …