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Editorial: Accelerating systems biology

Mazza, Tommaso
Briefings in Bioinformatics , Volume 11 (3): 267 Oxford University PressMay 1, 2010

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Editorial: Accelerating systems biology

Abstract

Editorial: Accelerating systems biology Over the years, the long-standing questions concerning disease evolution, plausible cellular behavior and the hidden properties of organisms have become more and more pressing. They sparked a movement of experts from an array of scientific areas and stimulated them to work cooperatively with the ambitious aim of deciphering the language of nature. From the onset, the field of genomics has been built on many important discoveries beginning with the DNA double helix structure in the 1950s, reverse transcriptase in the late 1960s, recombinant DNA and restriction enzymes in the 1970s, and finally, the polymerase chain reaction discovery in the early 1980s. For some time the polymerase chain reaction was particularly revolutionary because it was the only method used to determine the base sequence of DNA. Wishing to understand how key components ‘converse’ in time, space and across multiple organizational levels became one of the driving factors that led scientists to sequence large eukaryotic genomes, such as that of human, and to the discovery of more than 20 000 different genes and of nearly a million proteins within the cell. The transition years between the 1990s and first decade of the 2000s were the time of the collection of such results that were later mathematically formalized and summarized in artificial wired diagrams. Soon after, the idea that the full understanding could be possible by a holistic rather than by an atomistic approach became slowly appealing. Investigation on the assembly of the cell’s elementary parts to form complex structures represented the main activity of a promising new research field named ‘Systems Biology’. Progress in this area required interdisciplinary breakthroughs and close links between wet and dry experimentations. Due to an enormous eager interest, synthetic formalizations (or models) … Full Text of this Article
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Title
Editorial: Accelerating systems biology
Author(s)
Mazza, Tommaso
Journal
Briefings in Bioinformatics , Volume 11 (3): 267 Oxford University Press – May 1, 2010
Publisher
Oxford University Press
Copyright
Copyright © 2010 Oxford University Press
ISSN
1467-5463
eISSN
1477-4054
D.O.I.
10.1093/bib/bbq012
Publisher site
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