November 15, 2011 | Guest Commentary | Systems biology lies at the very heart of modern biomedical research and a number of review articles and conferences have caught the spirit of this movement. The discipline encompasses an assortment of related but distinct concepts, including the idea that detailed and comprehensive data from living systems will enable robust prediction of their trajectory and also the paradoxical notion that some biological behaviors occur in a relatively surprising and unexpected fashion, so-called emergent properties.
However, the ideas underlying systems biology are not new. First articulated by a number of researchers in the 1960s, some of the principal notions were also articulated by Francis Crick in a visionary Nature review article in 1970 that anticipated the state of molecular biology in the year 2000. In his article (Nature 228, 613-615 (Nov 1970)), Crick stated that “problems involving complex interactions can hardly be avoided… a simple example would be the ‘total’ behavior of a microorganism such as Escherichia coli, including all of its regulatory mechanisms.”
More recently, the systems biology agenda has been resurrected by Leroy Hood with his founding of the Institute for Systems Biology in Seattle (see “All Systems Go at ISB,” Bio·IT World, June 2002). This signal event has been followed by a growing body of work from the institute as well as several other groups.
The renaissance of systems biology has depended upon the dramatic advent of new and interrelated genetic and genomic technologies that gather biological data with ever increasing speed. The midwives of systems biology are thus the accompanying “omics” technologies, such as transcriptomics, proteomics and interactomics. At first, the large amount of data obtained by these omics technologies was impressive in its own right. More recently, however, there has been a tangible sense that mindless accumulation of data is insufficient, and that new insights are required if the discipline is to thrive. This disquiet has been exemplified by criticisms likening systems biology to a Stalinist five-year plan that will ultimately fall flat on its face.
Personally, I am not so sure and would like to throw back at the critics a quotation attributed to the Generalissimo: “Quantity has a quality all its own.”
Nevertheless, it does seem that the term systems biology is (already) becoming a bit tired despite the importance of the subject matter. The half-life of excitement for new disciplines does seem to get shorter with each passing year. After all, molecular biology was a good enough term for a topic that thrived for a couple of decades at least, while the term functional genomics seems like a distant memory, even though only a few years old.
Bring on the New
So, what would be a fresh and evocative new term for systems biology? The difficulty of developing an acceptable name reflects the broad landscape of this discipline. One recent suggestion from Eric Schadt is multiscale biology, referring to the diverse nature of the data used to construct models in systems biology. (Schadt is the new director of an institute dedicated to genomics and multiscale biology at Mt Sinai School of Medicine; see, “Partnering on Multiscale Biology,” Bio•IT World, July 2011)
However, a few other alternatives do present themselves.
- Biosignal processing is an attractive possibility. This name forges an analogy between the concepts underlying systems biology and electronic signal processing, except that the signals are biological (transcripts, proteins, nerve impulses etc.) instead of electrical.
- Biowireomics would emphasize the notion of integrating biological wiring diagrams from many diverse domains.
- In the same vein, bitomics emphasizes the now commonplace observation that biology is an information science.
- Another possibility is Tukomics, in honor of John Tukey, coiner of the term “bit,” while Shannomics would honor the father of information theory, Claude Shannon.
- Other instances that share the same sentiment are dataomics (because systems biology is concerned with integrating all relevant data types), totalomics (same sentiment) and kitchensinkomics (same sentiment, tongue-in-cheek). And of course, understandomics, because surely that is the final goal of systems biology.
But other fields are also overdue for a name modification. One instance that immediately springs to mind is nanotechnology. However, those scientists with young children know that finding affordable, scalable childcare represents a much more fundamental challenge for modern biomedical research.
Desmond J. Smith is a professor in the Dept. Molecular and Medical Pharmacology at UCLA. Email: DSmith@mednet.ucla.edu
This article also appeared in the November-December 2011 issue of Bio-IT World magazine. Subscribe today!