Hujun Yin; David Camacho; Peter Tino; Antonio J. Tallón-Ballesteros; Ronaldo Menezes; Richard Allmendinger Springer Nature Switzerland AG (2019) Pehmeäkantinen kirja
Hujun Yin; David Camacho; Peter Tino; Antonio J. Tallón-Ballesteros; Ronaldo Menezes; Richard Allmendinger Springer Nature Switzerland AG (2019) Pehmeäkantinen kirja
Hugo Barbosa (ed.); Jesus Gomez-Gardenes (ed.); Bruno Gonçalves (ed.); Giuseppe Mangioni (ed.); Ronaldo Menezes (ed.); Oliv Springer (2020) Kovakantinen kirja
Hugo Barbosa (ed.); Jesus Gomez-Gardenes (ed.); Bruno Gonçalves (ed.); Giuseppe Mangioni (ed.); Ronaldo Menezes (ed.); Oliv Springer (2021) Pehmeäkantinen kirja
Diogo Pacheco (ed.); Andreia Sofia Teixeira (ed.); Hugo Barbosa (ed.); Ronaldo Menezes (ed.); Giuseppe Mangioni (ed.) Springer (2023) Kovakantinen kirja
Andreia Sofia Teixeira (ed.); Federico Botta (ed.); José Fernando Mendes (ed.); Ronaldo Menezes (ed.); Giuseppe (e Mangioni Springer (2023) Kovakantinen kirja
Diogo Pacheco (ed.); Andreia Sofia Teixeira (ed.); Hugo Barbosa (ed.); Ronaldo Menezes (ed.); Giuseppe Mangioni (ed.) Springer (2024) Pehmeäkantinen kirja
Andreia Sofia Teixeira (ed.); Federico Botta (ed.); José Fernando Mendes (ed.); Ronaldo Menezes (ed.); Giuseppe (e Mangioni Springer (2024) Pehmeäkantinen kirja
Though the reductionist approachto biology and medicine has led to several imp- tant advances, further progresses with respect to the remaining challenges require integration of representation, characterization and modeling of the studied systems along a wide range of spatial and time scales. Such an approach, intrinsically - lated to systems biology, is poised to ultimately turning biology into a more precise and synthetic discipline, paving the way to extensive preventive and regenerative medicine [1], drug discovery [20] and treatment optimization [24]. A particularly appealing and effective approach to addressing the complexity of interactions inherent to the biological systems is provided by the new area of c- plex networks [34, 30, 8, 13, 12]. Basically, it is an extension of graph theory [10], focusing on the modeling, representation, characterization, analysis and simulation ofcomplexsystemsbyconsideringmanyelementsandtheirinterconnections.C- plex networks concepts and methods have been used to study disease [17], tr- scription networks [5, 6, 4], protein-protein networks [22, 36, 16, 39], metabolic networks [23] and anatomy [40].