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Abstract Systems biology is an approach by which biological questions are addressed through integrating experiments with computational modeling and theory in a reinforcing cycle. Systems biology can be described as a discipline that seeks to quantify and annotate complexity in biological systems in order to construct models with which we can predict outcomes from inputs. Systems biomedicine is an extension of these strategies into the study of biomedical problems. In the last decade, some significant changes occurred in different biomedical areas with the introduction of systems biology. Whereas at the present systems biology aims at modeling exhaustive networks (genetic networks, signal transduction pathways and metabolic network) of interactions, systems biomedicine emphasizes the multilevel hierarchical nature (cell, tissue, organ, organism and population) of the models. Examples are given to show how the problems are tackled in systems biomedicine. Analysis with mathematical models provides insight into complex diseases such as cancer, Alzheimer’s, Aids etc. Multilayered complexity at different levels (cell, organ, organism and population) challenges mathematical solutions, and computational software tools and database provisions. It is likely that in future new mathematics and computational tools will be required to deal with these complexities.

Keywords: Database, Mathematical Modeling, Systems biology, Systems Biomedicine

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