2009-08-05
AUTHORS ABSTRACTProgramming and software engineering are not new disciplines. Although software engineering has under gone shifts in philosophy, the fundamental mechanism used for defining the logic within a system is still the same as it was decades ago. Advances in languages and constructs have made the development of software easier and have reduced development time. Each successive generation of programming languages has obtained this simplification by introducing further abstractions away from the complexities of generating machine specific instructions required to actually run an executable within or across operating systems. These advances are still occurring today, and we are now able to develop more complex programs more rapidly than at any time in the past. This rapid progression has empowered the scientific developer, as modern experimental driven biological science requires the rapid development of algorithms and systems. Biology, in all its forms, is fundamentally an observational and experimental science. Whether it be ecology, neuroscience, clinical studies, or molecular biology, the high volumes of semantically rich large biological data sets require a high level of software development. This means that the software must be developed to a high standard and in a minimal amount of time. Therefore, to meet the demands of developing software to support research, the scientific developer must know about the latest tools and techniques. This chapter introduces some of these tools and techniques, in particular those that will help in the development of data intensive applications. More... »
PAGES403-440
Bioinformatics
ISBN
978-0-387-92737-4
978-0-387-92738-1
http://scigraph.springernature.com/pub.10.1007/978-0-387-92738-1_19
DOIhttp://dx.doi.org/10.1007/978-0-387-92738-1_19
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