Bisque: A Scalable Biological Image Database and Analysis Framework - High-Throughput Image Reconstruction and Analysis - page 297

Figure 13.7 Bisque analysis prototype: The nuclei counting analysis generates an interface based
on the module parameters. Parameters may be read from the image tags or from the user interface.
Results of the analysis can be stored as tags for review or further analysis.
ing scheme, thus allowing different index structures and search algorithms
to be integrated.
Most services use a RESTful architecture, which exposes resources through
URIs instead of functional services such as XML-RPC and SOAP. In a restful
architecture, resources are manipulated by using the standard HTTP verbs (GET,
PUT, POST, DELETE, and HEAD). There are many benefits attributed to building
Web services using the RESTful pattern, including scalability through Web caches,
and the use of client side state. Based on our experience, we expect that all Bisque
services and extensions will be built as component Web services allowing easy
recombination and reutilization by virtue of their language and tool independence.
13.3.4 Analysis Framework
The Bisque system functionality is extensible in several different ways. The sim-
plest mechanism for adding functionality is through the analysis modules. Analysis
modules interact with other components of the Bisque system (i.e., the data server
and the image server). Our framework allows an analysis to be written in any