TY - JOUR
T1 - An Early Stage Researcher’s Primer on Systems Medicine Terminology
AU - Zanin, Massimiliano
AU - Atiya, Nadim
AU - Basilio, Jose
AU - Baumbach, Jan
AU - Benis, Arriel
AU - Behera, Chandan
AU - Bucholc, Magda
AU - Castiglione, Filippo
AU - Chouvarda, Ioanna
AU - Comte, Blandine
AU - Dao, Tien-Tuan
AU - Ding, Xuemei
AU - Pujos-Guillot, Estelle
AU - Filipovic, Nenad
AU - Finn, David
AU - Glass, David H.
AU - Harel, Nissim
AU - Iesmantas, Tomas
AU - Ivanoska, Ilinka
AU - Joshi, Alok
AU - Boudjeltia, Karim
AU - Kaoui, Badr
AU - Kaur, Daman
AU - Maguire, Liam
AU - McClean, Paula
AU - McCombe, Niamh
AU - Luis de Miranda, Joao
AU - Moisescu, Mihnea
AU - Pappalardo, Francesco
AU - Polster, Annikka
AU - Prasad, Girijesh
AU - Rozman, Damjana
AU - Sacala, Ioan
AU - Sanchez Bornot, Jose
AU - Schmid, Johannes
AU - Sharp, Trevor
AU - Solé-Casals, Jordi
AU - Spiwok, Vojtěch
AU - Spyrou, George
AU - Stalidzans, Egils
AU - Stres, Blaz
AU - Sustersic, Tijana
AU - Symeonidis, Ioannis
AU - Tieri, Paolo
AU - Todd, Stephen
AU - van Steen, Kristel
AU - Veneva, Milena
AU - Wang, Da-Hui
AU - Wang, Haiying / HY
AU - Wang, Hui
AU - Watterson, Steven
AU - Yang, Su
AU - Zou, Xin
AU - Wong-Lin, KongFatt
AU - Schmidt, Harald
N1 - © Massimiliano Zanin et al., 2021; Published by Mary Ann Liebert, Inc.
PY - 2021/2/25
Y1 - 2021/2/25
N2 -
Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields.
Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references.
Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic.
AB -
Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields.
Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references.
Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic.
KW - Genetics
KW - Graphs and Networks
KW - machine learning
KW - medicine
KW - Systems medicine
KW - multi-scale modelling
KW - multi-scale data science
U2 - 10.1089/nsm.2020.0003
DO - 10.1089/nsm.2020.0003
M3 - Review article
C2 - 33659919
SN - 2690-5949
VL - 4
SP - 2
EP - 50
JO - Network and Systems Medicine
JF - Network and Systems Medicine
IS - 1
ER -