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Editorial Focus
Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin
THIS ISSUE OF Physiological Genomics contains an invited Editorial emphasizing the enormous importance of and the role that computational modeling must play in the synthesis of mechanistically based hypotheses of complex biological systems. It is remarkable that in the short life of our journal (
5 yrs), the Human Genome Project has been completed and more than 25 other genomes have been sequenced, ranging from fungus to the mouse and rat. Efficient and affordable high-throughput technologies are now commonplace at most universities for determining gene expression and for gene sequencing. The same can be said of transgenic facilities and viral vector laboratories for modification of genes and their expression. Although proteomics has not yet achieved this level of efficiency, the technologies for protein identification and quantification are rapidly advancing.
Less than a decade ago, everyone was scrambling to train and hire computer experts that could manage the huge data sets produced by microarray analyses and the linkage results of whole genome scans. This was quickly accommodated by the parallel training of biology students in fields of computer technology. Bioinformatic centers quickly sprang up around the high-throughput biology laboratories to accommodate the management and analysis of these large data sets. These events have resulted in enormous progress in describing genomic events in normal and stressed states of organisms.
From the onset of the application of these high-throughput approaches, it was recognized that the goal of this work was not merely warehousing large data sets. As emphasized in a perspective by A. Hastings and M. A. Palmer (1), thoughtful scientists know that the hard work is yet ahead and that relevance of this work rests on our ability to use these data sets to achieve a mechanistic understanding of complex cellular and organismic functions. As inevitably occurs in science, a new breed of scientists, computational biologists, is emerging to fill this timely and vital need. Computer modeling is not a new idea, but the need for these approaches has never been greater. If empowered with appropriate resources, this new generation of researchers, working in close collaboration with bench scientists, will begin to provide unifying conceptual frameworks of biological systems built upon solid biophysical principles.
The Editorial by Beard, Bassingthwaighte, and Greene in this issue of Physiological Genomics represents what I hope will be an important direction for the type of research to be increasingly published in this journal. From the beginning of Physiological Genomics, we have encouraged publication of new computational approaches and integrative models to link genes to complex function. During the remainder of this year and beyond, our goal is to feature such work to the extent possible.
FOOTNOTES
Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).
Address for reprint requests and other correspondence: A. W. Cowley, Jr., Dept. of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226 (e-mail: pgeditor{at}mcw.edu).
REFERENCES
This article has been cited by other articles:
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  M. Liang and B. Ventura Physiological genomics in PG and beyond: July to September 2005 Physiol Genomics, October 17, 2005; 23(2): 119 - 124. [Full Text] [PDF]
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