Collaboration - Bioinformatics Computing - page 343

commercial Celera Genomics often overshadows the remarkable fact that the former involved the
collaboration of 20 laboratories in 6 countries. Although academics in the bioinformatics field struggle
for tenure, publications, and discoveries just as vehemently as researchers in other fields of
academia, bioinformatics is characterized by an unusually high degree of collaboration among the
researchers seeking to further the fields of genomics and proteomics.
At least part of the reason for this level of cooperation is the reward system established for sharing
data. Virtually all molecular biology journals require authors to submit the sequence or structure
described in their manuscripts to public databases prior to publication. What's more, unlike only a
decade ago, many universities now consider software development as a type of publication worth
consideration when the author is up for promotion or tenure. Another factor is that, unlike other
fields such as nuclear physics, where the results of some multi-billion dollar experiment is put into
the hands of perhaps a dozen scientists to evaluate, there is a flood of data that couldn't possibly be
handled in a dozen scientist's lifetimes. Without the thousands of investigators developing tools and
analyzing sequences and structures as they are generated, the field would be at a standstill. Perhaps
everyone realizes that there's more than enough data and associated challenges to go around, and
that it's only through cooperation and parallel exploration that the full potential of genomics and
proteomics can be realized in our lifetimes.
This chapter explores the technologies and processes that can be used to facilitate collaboration in
bioinformatics, starting with the " Collaboration and Communications " section, which distinguishes
between communications and collaboration on the basis of technology, introduces many of the
concepts underlying communications and collaboration, and focuses on real-time versus
asynchronous methods. The remainder of the chapter deals with the issues underlying
communications in bioinformatics. For example, the " Open Source " section looks at how the rise in
popularity of open-source software has made a major impact on the development of bioinformatics
programs. " Standards " explores the role of standards in bioinformatics, from file formats to operating
systems, and their affect on day-to-day operations. Finally, the " On the Horizon " and " Endnote "
sections consider the future of communications and the role of commercialization in making many of
the dreams in bioinformatics research a reality.