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2016 ; 14
(1
): 324
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Bridging the gap between clinicians and systems biologists: from network biology
to translational biomedical research
#MMPMID27876057
Jinawath N
; Bunbanjerdsuk S
; Chayanupatkul M
; Ngamphaiboon N
; Asavapanumas N
; Svasti J
; Charoensawan V
J Transl Med
2016[Nov]; 14
(1
): 324
PMID27876057
show ga
With the wealth of data accumulated from completely sequenced genomes and other
high-throughput experiments, global studies of biological systems, by
simultaneously investigating multiple biological entities (e.g. genes,
transcripts, proteins), has become a routine. Network representation is
frequently used to capture the presence of these molecules as well as their
relationship. Network biology has been widely used in molecular biology and
genetics, where several network properties have been shown to be functionally
important. Here, we discuss how such methodology can be useful to translational
biomedical research, where scientists traditionally focus on one or a small set
of genes, diseases, and drug candidates at any one time. We first give an
overview of network representation frequently used in biology: what nodes and
edges represent, and review its application in preclinical research to date.
Using cancer as an example, we review how network biology can facilitate
system-wide approaches to identify targeted small molecule inhibitors. These
types of inhibitors have the potential to be more specific, resulting in high
efficacy treatments with less side effects, compared to the conventional
treatments such as chemotherapy. Global analysis may provide better insight into
the overall picture of human diseases, as well as identify previously overlooked
problems, leading to rapid advances in medicine. From the clinicians' point of
view, it is necessary to bridge the gap between theoretical network biology and
practical biomedical research, in order to improve the diagnosis, prevention, and
treatment of the world's major diseases.
free
free
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