Biomedical Engineering Reference
In-Depth Information
company. Critically, SMW understands hierarchies, so if the user were
to view the same page for 'phosphodiesterases' they would see all
such proteins, including the four shown here. Similar views have been
set up for pathway, disease and Gene Ontology functions, providing
a powerful mechanism for looking across the data - and all (almost),
for free!
Collaboration in Targetpedia
One of the major differences between Targetpedia and our legacy protein/
target information systems are features that empower internal
collaboration. For instance, Pfi zer drug discovery project tracking codes
are found on all pages that represent internal targets, providing an easy
link to business data. Each project code has its own page within
Targetpedia, listing the current status, milestones achieved and,
importantly, the people associated with the research. The connection of
projects to scientists was made possible thanks to the corporate timesheets
that all Pfi zer scientists complete each week, allocating their time against
specifi c project codes. By integrating this into Targetpedia, this
administrative activity moves from simply a management tool to
something that tangibly enables collaboration. Further integration
with departmental information systems provides lists of colleagues
involved in the work, organised by work area. This helps users of
Targetpedia fi nd not just the people involved, but those from say, the
pharmacodynamics or high-throughput screening groups. We believe
this provides a major advance in helping Pfi zer colleagues fi nd the
right person to speak to regarding a project on a target in which they
have become interested.
A second collaboration mechanism revolves around the concept of the
'idea portfolio'. We wanted to make it very easy for users to assert an
interest in a particular protein. Similar to the Facebook 'like' function,
the fi rst button in the tagging bar (Figure 17.3) allows users to 'Tag (this
protein) as my target' with a single click. This makes it trivial for scientists
to create a portfolio of proteins of interest to them or their research unit.
An immediate benefi t is access to a range of alerting tools, providing
email or RSS updates to new updates, database entries or literature
regarding their chosen proteins. However, the action of tagging targets
creates a very rich data set that can be exploited to identify connections
between disparate individuals in a global organisation. Interest in the
same target is obvious, but as mentioned above, algorithms that scan the
connections to identify colleagues with interests in different proteins but
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