Systems Biology: The Big Picture

Spivey, Angela

doi:10.1289/ehp.112-a938

Cited by 17 publications

(9 citation statements)

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“…Cells use sophisticated mechanisms to functionally connect their molecules and machineries with the aim of activating, sustaining and modulating their critical functions: survival, growth, proliferation, differentiation, and death [ 1 , 2 ]. Following the characterization of very complex cross-talks among the different signalling cascades, a molecular network view of cell biology and physiology has emerged together with the concept of Biological Complex Systems [ 3 ]. The ultimate outcome of this structural and functional organization is the metabolism of organisms and their cells.…”

Section: Introductionmentioning

confidence: 99%

The apoptotic machinery as a biological complex system: analysis of its omics and evolution, identification of candidate genes for fourteen major types of cancer, and experimental validation in CML and neuroblastoma

et al. 2009

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Section: Introductionmentioning

confidence: 99%

The apoptotic machinery as a biological complex system: analysis of its omics and evolution, identification of candidate genes for fourteen major types of cancer, and experimental validation in CML and neuroblastoma

et al. 2009

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“…The NIEHS Portal aims to facilitate, among other things, knowledge networking within communities by creating task- and domain-specific ontologies that can be used for applied purposes. The development of such ontologies must be participatory in so far as it requires a common language that cuts across disciplines and professional boundaries (Spivey 2004). …”

Section: Context and Methodsmentioning

confidence: 99%

The NIEHS Environmental Health Sciences Data Resource Portal: Placing Advanced Technologies in Service to Vulnerable Communities

Pezzoli¹,

Tukey²,

Sarabia³

et al. 2007

Environ Health Perspect

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BackgroundTwo devastating hurricanes ripped across the Gulf Coast of the United States during 2005. The effects of Hurricane Katrina were especially severe: The human and environmental health impacts on New Orleans, Louisiana, and other Gulf Coast communities will be felt for decades to come. The Federal Emergency Management Agency (FEMA) estimates that Katrina’s destruction disrupted the lives of roughly 650,000 Americans. Over 1,300 people died. The projected economic costs for recovery and reconstruction are likely to exceed $125 billion.ObjectivesThe NIEHS (National Institute of Environmental Health Sciences) Portal aims to provide decision makers with the data, information, and the tools they need to a) monitor human and environmental health impacts of disasters; b) assess and reduce human exposures to contaminants; and c) develop science-based remediation, rebuilding, and repopulation strategies.MethodsThe NIEHS Portal combines advances in geographic information systems (GIS), data mining/integration, and visualization technologies through new forms of grid-based (distributed, web-accessible) cyberinfrastructure.ResultsThe scale and complexity of the problems presented by Hurricane Katrina made it evident that no stakeholder alone could tackle them and that there is a need for greater collaboration. The NIEHS Portal provides a collaboration-enabling, information-laden base necessary to respond to environmental health concerns in the Gulf Coast region while advancing integrative multidisciplinary research.ConclusionsThe NIEHS Portal is poised to serve as a national resource to track environmental hazards following natural and man-made disasters, focus medical and environmental response and recovery resources in areas of greatest need, and function as a test bed for technologies that will help advance environmental health sciences research into the modern scientific and computing era.

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“…The ability to perform experiments, and the use of increasing computational power to develop better in silico models, at systems level, played an important role in this process. However, an early attempt to apply developments in those areas to molecular networks involved in disease, in the form of ‘systems biology’ ( Lazebnik, 2002 ; Powell, 2004 ; Spivey, 2004 ), got slowed down by a few fundamental challenges. The effort and time needed to advance our understanding of all relevant system components and their interactions in human health, at sufficient detail for determining the best intervention (i.e.…”

Section: Systems Approachesmentioning

confidence: 99%

“…Such omics technologies now exist for many different levels of biological systems, including DNA, variants for RNA, protein and metabolite-level system dynamics (i.e. genomics, transcriptomics, proteomics, and metabolomics; Spivey, 2004 ). Depending on the sample we take and how we process it, omics technologies can generate very rich datasets about the ‘expression state’ of thousands of molecules in those systems (that are represented by the samples that were taken).…”

Section: Successful Paradigms From Leading Areas Of Health Innovatiomentioning

confidence: 99%

Towards a systems approach for chronic diseases, based on health state modeling

Rebhan

2017

F1000Res

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Rising pressure from chronic diseases means that we need to learn how to deal with challenges at a different level, including the use of systems approaches that better connect across fragments, such as disciplines, stakeholders, institutions, and technologies. By learning from progress in leading areas of health innovation (including oncology and AIDS), as well as complementary indications (Alzheimer’s disease), I try to extract the most enabling innovation paradigms, and discuss their extension to additional areas of application within a systems approach. To facilitate such work, a Precision, P4 or Systems Medicine platform is proposed, which is centered on the representation of health states that enable the definition of time in the vision to provide the right intervention for the right patient at the right time and dose. Modeling of such health states should allow iterative optimization, as longitudinal human data accumulate. This platform is designed to facilitate the discovery of links between opportunities related to a) the modernization of diagnosis, including the increased use of omics profiling, b) patient-centric approaches enabled by technology convergence, including digital health and connected devices, c) increasing understanding of the pathobiological, clinical and health economic aspects of disease progression stages, d) design of new interventions, including therapies as well as preventive measures, including sequential intervention approaches. Probabilistic Markov models of health states, e.g. those used for health economic analysis, are discussed as a simple starting point for the platform. A path towards extension into other indications, data types and uses is discussed, with a focus on regenerative medicine and relevant pathobiology.

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Systems Biology: The Big Picture

Cited by 17 publications

References 0 publications

The apoptotic machinery as a biological complex system: analysis of its omics and evolution, identification of candidate genes for fourteen major types of cancer, and experimental validation in CML and neuroblastoma

The apoptotic machinery as a biological complex system: analysis of its omics and evolution, identification of candidate genes for fourteen major types of cancer, and experimental validation in CML and neuroblastoma

The NIEHS Environmental Health Sciences Data Resource Portal: Placing Advanced Technologies in Service to Vulnerable Communities

Towards a systems approach for chronic diseases, based on health state modeling

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