Systems medicine disease : disease classification and scalability beyond networks and boundary conditions
In order to accommodate the forthcoming wealth of health and disease related information, from genome to body sensors to population and the environment, the approach to disease description and definition demands re-examination. Traditional classification methods remain trapped by history; to provide...
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sg-ntu-dr.10356-895812020-11-01T05:31:13Z Systems medicine disease : disease classification and scalability beyond networks and boundary conditions Berlin, Richard Gruen, Russell Best, James Lee Kong Chian School of Medicine (LKCMedicine) Systems Medicine Disease DRNTU::Science::Medicine In order to accommodate the forthcoming wealth of health and disease related information, from genome to body sensors to population and the environment, the approach to disease description and definition demands re-examination. Traditional classification methods remain trapped by history; to provide the descriptive features that are required for a comprehensive description of disease, systems science, which realizes dynamic processes, adaptive response, and asynchronous communication channels, must be applied (Wolkenhauer et al., 2013). When Disease is viewed beyond the thresholds of lines and threshold boundaries, disease definition is not only the result of reductionist, mechanistic categories which reluctantly face re-composition. Disease is process and synergy as the characteristics of Systems Biology and Systems Medicine are included. To capture the wealth of information and contribute meaningfully to medical practice and biology research, Disease classification goes beyond a single spatial biologic level or static time assignment to include the interface of Disease process and organism response (Bechtel, 2017a; Green et al., 2017). Published version 2018-10-12T04:39:08Z 2019-12-06T17:28:52Z 2018-10-12T04:39:08Z 2019-12-06T17:28:52Z 2018 Journal Article Berlin, R., Gruen, R., & Best, J. (2018). Systems Medicine Disease: Disease Classification and Scalability Beyond Networks and Boundary Conditions. Frontiers in Bioengineering and Biotechnology, 6, 112-. doi:10.3389/fbioe.2018.00112 https://hdl.handle.net/10356/89581 http://hdl.handle.net/10220/46298 10.3389/fbioe.2018.00112 en Frontiers in Bioengineering and Biotechnology © 2018 Berlin, Gruen and Best. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. 13 p. application/pdf |
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Systems Medicine Disease DRNTU::Science::Medicine Berlin, Richard Gruen, Russell Best, James Systems medicine disease : disease classification and scalability beyond networks and boundary conditions |
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In order to accommodate the forthcoming wealth of health and disease related information, from genome to body sensors to population and the environment, the approach to disease description and definition demands re-examination. Traditional classification methods remain trapped by history; to provide the descriptive features that are required for a comprehensive description of disease, systems science, which realizes dynamic processes, adaptive response, and asynchronous communication channels, must be applied (Wolkenhauer et al., 2013). When Disease is viewed beyond the thresholds of lines and threshold boundaries, disease definition is not only the result of reductionist, mechanistic categories which reluctantly face re-composition. Disease is process and synergy as the characteristics of Systems Biology and Systems Medicine are included. To capture the wealth of information and contribute meaningfully to medical practice and biology research, Disease classification goes beyond a single spatial biologic level or static time assignment to include the interface of Disease process and organism response (Bechtel, 2017a; Green et al., 2017). |
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Lee Kong Chian School of Medicine (LKCMedicine) |
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Lee Kong Chian School of Medicine (LKCMedicine) Berlin, Richard Gruen, Russell Best, James |
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Article |
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Berlin, Richard Gruen, Russell Best, James |
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Berlin, Richard |
title |
Systems medicine disease : disease classification and scalability beyond networks and boundary conditions |
title_short |
Systems medicine disease : disease classification and scalability beyond networks and boundary conditions |
title_full |
Systems medicine disease : disease classification and scalability beyond networks and boundary conditions |
title_fullStr |
Systems medicine disease : disease classification and scalability beyond networks and boundary conditions |
title_full_unstemmed |
Systems medicine disease : disease classification and scalability beyond networks and boundary conditions |
title_sort |
systems medicine disease : disease classification and scalability beyond networks and boundary conditions |
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2018 |
url |
https://hdl.handle.net/10356/89581 http://hdl.handle.net/10220/46298 |
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