Biomedical Engineering Reference
In-Depth Information
to build on this success and allow further information to be added and
tracked through the DMTA cycle as well as methods for creating different
views into the data.
12.2 Methods
Computational chemistry groups have long had access to Linux
environments; it is core to the specialist software used in this fi eld. Compared
with the corporate Windows environment, Linux workstations and server
systems may be fewer in number. Being dedicated to small R&D groups,
there is generally far greater freedom to exploit their full functionality, such
as running Apache web servers [3]. This is how we fi rst started to explore
web-based applications via Apache on our Linux network. As the
technologies behind web sites have developed so have our web sites. Initial
HTML hand-coded web sites have been replaced by wikis and content
management systems. Although the end result is more functional and Web
2.0-like web sites, they are also far more complicated, utilising databases
and multiple frameworks (Javascript, CSS and Ajax, etc.).
Traditionally, all of our applications are thick clients - this works well
for our vendors. In-house code tends to primarily consist of scripts or
command-line binaries, optimised to run on our high performance
computing (HPC) clusters. We do have some GUI applications, but the
effort to build a GUI is not trivial. Using web sites offers GUI-like
functionality with relative ease. HTML tables are ugly but they can be
populated from a database using Perl or Python [4]. New web technologies
such as DataTables enable interactive tables [5]. Graphing is another
example of improvement. We do not want to write and maintain graph
libraries for each language we use. Originally we used Emprise Javascript
Charts [6], but have switched from this commercial licence to the open
source fl ot library [7]. The move was partly motivated by functionality
we needed already being present in fl ot. An important aspect for
pharmaceutical research is the visualisation of molecules. We are now in
the fortunate position to have a multitude of chemistry toolkits to assist.
Like the graphing libraries we have no desire to write our own chemistry
toolkit. The combination of libraries and toolkits available mean that
computational chemists can pick them up and make something to suit
our specifi c needs. Our output is typically intended for our local users or
for the computational chemistry community throughout the company,
for example a relatively small number. Building web-based applications
means every R&D scientist can use our software, without the need for
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