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In the previous section, you saw how to allow fellow members of your Web team or clients to add whatever external style sheets they like. But what if you want to operate under more controlled circumstances and provide a set number of specific choices This is particularly important if you have painstakingly crafted CSS hacks for your style sheets. You may remember from 5 how a page was set up using JavaScript to allow the visitor to switch from one style sheet to another at run-time. In this section, you ll see how to set up a page to switch style sheets at design-time. The template feature contains some of Dreamweaver s least-known (but more powerful) capabilities, including a complete template expression language. One aspect of the template expression language enables Dreamweaver to insert certain code if a particular condition is met or a defined parameter is set at design time. The Multiple-If template expression is perfect for setting up a template so that a variety of preselected CSS style sheets can be applied. To demonstrate the potential of Multiple-If template expressions, let s construct the code necessary to choose between three different style sheets at design time. All of the following code is to be placed in the head area of the template outside of the head editable region. This placement locks the code against modification in all child pages. Whether you put it above or below the head editable region depends on your workflow as discussed in the previous section.

emergence of parallel computing, biological applications were developed that could take advantage of multiple processor architectures with distributed or shared memory and locally located disk space to execute a collection of tasks Applications that compute molecular structure or electronic interactions of a protein fragment are examples of programs developed to take advantage of emerging computational technologies As distributed memory parallel architectures became more prevalent, computational biologists became familiar with message passing library toolkits, rst with Parallel Virtual Machine (PVM) and more recently with Message Passing Interface (MPI) This enabled biologists to take advantage of distributed computational models as a target for executing applications whose structure is that of a pipelined set of stages, each dependent on the completion of a previous stage In pipelined applications, the computation involved for each stage can be relatively independent from the others.

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For example, one computer may perform molecular computations and immediately stream results to another computer for visualization and analysis of the data generated Another application scenario is that of a computer used to collect data from an instrument (say a tilt series from an electron microscope), which is then transferred to a supercomputer with a large shared memory to perform a volumetric reconstruction, which is then rendered on yet a different highperformance graphic engine The distribution of the application pipeline is driven by the number and the type of different tasks to be performed, the available architectures that can support each task, and the I/O requirements between tasks While the need to support these applications continues to be very important in computational biology, an emerging challenge is to support a new generation of applications that analyze and/or process immense amounts of input/output data.

In such applications, the computation on each of a large number of data points can be relatively small, and the results of an application are provided by the analysis and often visualization of the input/output data For such applications, the challenge to infrastructure developers is to provide a software environment that promotes application performance and can leverage large numbers of computational resources for simultaneous data analysis and processing In this chapter, we consider these new applications that are forming the next wave of computational biology 4012 The next wave: data-driven applications The next wave of computational biology is characterized by high-throughput, high technology, data-driven applications The focus on genomics, exempli ed by the human genome project, will engender new science impacting a wide spectrum of areas from crop production to personalized medicine And this is just the beginning.

3. Mr(v) is the n n matrix, which is equal to the identity matrix except that the element in position (r, s) of Mr(v) is v. For example, when n 4 1 B0 M4 (v) B @0 0 0 0 1 0 0 0 0 1 0 1 0 0C C: 0A v

The amount of raw DNA sequence being deposited in the public databases doubles every 6 to 8 months Bioinformatics and Computational Biology have become a prime focus of academic and industrial research The core of this research is the analysis and synthesis of immense amounts of data resulting in a new generation of applications that require information technology as a vehicle for the next generation of advances Bioinformatics grew out of the human genome project in the early 1990s The requests for proposals for the physical and genetic mapping of speci c chromosomes called for developments in informatics and computer science, not just for data management but for.

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