Biology Reference
In-Depth Information
Systems Biology
Cristian I. Ruse & John R. Yates III
The cell is the fundamental entity of a living organism. Four main
types of chemical compounds are essential for any living organism:
amino acids, fatty acids, nucleic acids, and sugars [1]. Fatty acids
form membranes (composed mainly of phospholipids) that in turn
define the physical space of a cell and mediate its interaction with the
environment. Hereditary information is stored in genes (made up by
nucleic acids). Proteins, which constitute more than 50% of the dry
weight of the cell, give the functional form of the genes. The cell draws
energy from sugar that can subsequently be stored both in fatty acids
and polysaccharides.
Omics technologies aim to indiscriminately analyze and characterize
genes (genomics/transcriptomics), proteins (proteomics), and metabo-
lites (metabolomics). Systems biology uses these large-scale strategies
to portray interactions among genes, gene products, and molecules
involved in interactions with their environment (i.e., metabolites,
lipids, carbohydrates, hormones, etc.). As the biological system reaches
another level of complexity by assembly of multicellular systems into
organs, metabonomics links the high-throughput technologies with
tissue histology by analyzing biological fluids and tissues [2].
Understanding how these components assemble in a living cell (or
any other physiological entity), communicate, and function requires
the ability to formulate and test hypotheses. Analytical chemistry pro-
vides the measurement tools and computational modeling supplies
the necessary framework to produce knowledge from the integration
of these measurements [3]. Systems biology analysis integrates experi-
mental data with a computational model; it uses the model to test how
predictions fit experimental observations and eventually allows for
generation of new hypotheses [4].
Mass spectrometry (MS), one of many tools used in analytical chem-
istry, has the ability to perform unbiased global analysis of the structure
and the quantity of almost all molecular components of a biological
system [5]. The goal of a large-scale MS experiment is to provide input
data for any type of computational model in systems biology, from
abstract (high-level) models to very detailed (low-level) ones [3]. MS can
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