Network Bioscience Volume II

Network biology is based on the intuition that the quantitative modeling and algorithmic tools of network theory offer new possibilities to understand, model, and simulate the cell's internal organization and evolution, fundamentally altering our view of cell biology. As network biology has been gaining ground and recognition in the last 20 years, the scope of its application, while still well grounded in molecular biology and genetics, has moved steadily from tackling fundamental biological questions towards translational medicine, including modeling of diseases and applications in drug design and drug action prediction.This Research Topic Network Bioscience Vol II follows in the track of the first one Network Bioscience completed in 2019 (Antoniotti et al., 2019), and it aims at collecting cutting-edge research on the many guises of network bioscience.The papers contained in the present Research Topic are examples of how network and graph analysis can be used to elucidate various aspects of biological systems from inferring missing annotations, handling heterogeneous data types, including the vast literature available online, understanding metabolic dynamics, phenotype-genotype linking, to relationships assessment among diverse omics data for drug design and drug repositioning, to a deeper understanding of modularity in gene networks.