Systems Approach to Understanding Oral Diseases

Systems Approach to Understanding Oral Diseases

Amit Chattopadhyay
Copyright: © 2010 |Pages: 17
DOI: 10.4018/978-1-60566-733-1.ch003
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Abstract

This chapter reviews the principles of systems biology and their application through computational methods (bioinformatics, computational biomodeling, genomics, proteomics, oral human microbiome, molecular modeling, systems biology, protein structure prediction, structural genomics, computational biochemistry and computational biophysics methods and projects) that have been applied to oral diseases research. The emphasis of the chapter is on concepts from molecular biology, genetics, and traditional pathology to provide new insights into oral diseases, and the associated technologies to provide new diagnostic, therapeutic and prognostic information. Another goal of the manuscript will be to serve as a central reference to access of information about systems biology resources for research into oral diseases.
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Biological Systems

Several types of biological systems can be described based on their inherent properties (Table 1). Biological systems are complex open systems for which four fundamental universal properties of complex biological systems have been recognized that are not are not apparent from study of the parts. These properties are: emergence, irreducibility, modularity and robustness.

Table 1.
Commonly used terms in context of systems biology (Adapted from Fisher & Henzinger, 2007)
BiomicsSystems analysis of the biome (climatically and geographically defined areas of ecologically similar climatic conditions such as communities of all types of life forms).
FluxomicsStudy that deals with the dynamic changes of molecules within a cell over time.
GenomicsStudy of the genomes of organisms.
GlycomicsStudy dealing with identification of the entirety of all carbohydrates in a cell or tissue.
InteractomicsStudy dealing mostly with protein-protein interactions but is also applicable to study of interactions between all molecules within a cell.
MetabolomicsStudy dealing with identification and measurement of all small-molecules metabolites within a cell or tissue.
ProteomicsStudy dealing with complete identification of proteins and protein expression patterns of a cell or tissue.
TranscriptomicsStudy dealing with whole cell or tissue gene expression measurements.
Closed systemA closed system is completely self-contained and is not modified by the environment.
Deterministic systemA deterministic system always has the same response to a particular stimulus under a set of conditions. Therefore, the output from such a system can always be predicted.
Distributed systemA distributed system consists of a collection of autonomous computers connected through a network of that enables them to coordinate their activities and to share the resources of the system so that users perceive the system as a single, integrated computing facility.
Nondeterministic systemA nondeterministic system has several different possible reactions to the same stimulus under the same set of conditions. Therefore, the output cannot be predicted from the input.
Non-reactive systemA non-reactive system carries on the same process irrespective of the changes in other processes.
Open systemAn open system is interacts with the environment and is modified by these environmental interactions.
Reactive systemA reactive system consists of parallel processes, where each process may change in reaction to another process changing its state.

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