Real time PCR - European Pharmaceutical Review

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2009 HIGH CONTENT SCREENING
nodes (configured, executed, ...) and
returns, on demand, a pool of
executable nodes. This way the
surrounding framework can freely
distribute the workload among a
couple of parallel threads or – in the
future – even a distributed cluster of
servers. Each Node can have an
arbitrary number of views associated
with it.
Plate Viewer
Plate Viewer (PV) guarantees the
identification of library and well
position of a specific compound on a
plate. The history of location of each
compound in the screen, run and
replicate along with reformatting
information are recorded and
reconstructed by PV. Within the
GUI the user may select the library,
plate and if desired, compounds
data derived from specific 96,
384 or 1536-well plate. Once a
plate is selected, a window is opened
in a plate viewer that provides
functions easy navigation within the
plate that helps extracting of
comprehensive information from
wells about particular compounds
(see Figure 5).
HiLite controls on the plate
Through receiving events from a
HiLiteHandler (and sending events to
it) it is possible to mark selected
points in such a view to enable visual
brushing. Views can range from
simple table views to more complex
views on the underlying data (e.g.
scatterplots, parallel coordinates) or
the generated model (e.g. decision
trees, rules).
Join library, image results, image
processing results
This node joins two or three data
sources in one matrix. The join on the
two sources is carried out so that the
first source table (from the first, top
input port) provides the left part of
the output table and the second table
(bottom input port) provides the
columns for the right part. Thus, the
output table has as many rows as
Figure 5: Plate viewer plug-in. Visualisation of image processing parameters in heatmap
with access to library metadata.
both of the input tables (given
that both tables contain exactly the
same row identifier (IDs)) and as
many columns as the sum of both
column counts. If a row ID only occurs
in one of the two tables, the remaining
part (the column that should have
been provided by the other table) is
filled with missing records.
Cluster support
Due to the modular architecture it is
easy to designate specific nodes to be
run on separate machines. But to
accommodate the increasing
availability of multi-core machines,
the support for shared memory
parallelism also becomes increasingly
important. KNIME offers a unified
framework to parallelise data parallel
operations. Sieb et al. (2007) 14
describe further extensions, which
enable the distribution of complex
tasks such as cross validation on a
cluster or a GRID.
Image processing nodes
Image processing can process sets of
images parallel. Of particular interest
to HCS assay development is the
ability to load sequences of images to
create what ImageJ15 calls a “Stack”.
We describe standard nodes of
HC/DC for image processing:
■ Data I/O: generic image file reader
and image writer which overwrite
■
■
■
■
images or create new output
collection of images
Image Selections: The ImageK
provides tools for selecting regular
and irregular areas (called Regions
Of Interest or ROIs) on an image.
Several types of selections such as
rectangles, circles, poly-line, and a
“magic wand” are available.
Selections can be measured,
filtered, filled or drawn
Colour and level adjustment: Basic
brightness/contrast and
minimum/maximum level
adjustments are available as
nodes. This includes the allowance
for colour adjustments by
separately manipulating R, G, and
B (as well as C, M, and Y)
Other image adjustments: A range
of standard image adjustments
such as rotation, resizing (with or
without interpolation), cropping,
duplicating, zooming, and
renaming are fully supported
Image Filtering: Several standard
image filters are included in ImageK.
Some of these include “Gaussian
Blur”, “Median”, “Mean”, and
“Unsharp Mask”, among others.
There is also the built in capability
of specifying a user-defined
convolution mask. Dozens of
user-contributed plugins provide
access to many other filters
including Wavelet filters. Fourier
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