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Comparing apples to Apples
April 2012
EDIT CONNECT
SHARING OPTIONS:
SAN FRANCISCO—IO Informatics, a leader in semantic data
integration and knowledge management for life
sciences and healthcare, will
partner with Sage-N Research
Inc., a company that specializes in computational
proteomics, in an agreement announced last month.
The combination of the two companies' technologies creates a
semantic application framework that is being used to quickly develop a highly
specialized, large-scale application that leverages mass-spectrometry based
proteomics with "unmatched content enrichment, interoperability and
flexibility
only possible with semantic data integration," the release announcing the
partnership states.
"Semantic data integration means putting data in context,"
explains Dr. Erich Gombocz, IO's chief scientific officer. "I use the
example
of an apple. 'How much does an apple cost?' is totally dependent on if you mean
the fruit or the computer; without that context, you really
cannot answer this
question. The same holds true in a much more stringent way for biological data;
data out of context is isolated and of no actionable
use, but data in context
of other data provides the meaningful underlying framework to understand
complex interactive and interrelated intricate
biological processes on a
systems level. Because our technology is based on the Resource Description
Framework, its data structure does not require
predefined schemas, but is based
in its entirety on triples—sets of resources commonly described in form of 'A
is related to B' (or, more formally,
as subject, predicate, object). Data
becomes aware of their surroundings—they are 'sentient' of how to connect and
what they mean in their context,
thus the name of IO's tools, 'Sentient Suite.'
Because of this dynamic extensible and data-container agnostic framework, data
can be mapped to
ontological concepts and are easily reconfigured to changing
scientific needs."
Most
importantly, Gombocz believes, since a semantic
knowledge base is a network graph of data in their relationships with each
other, it enables discovery
of pattern-based relationship clusters and
interactions that were not previously apparent. Graphic icons represent
proteins, diseases and organisms,
for example, with the colors and thicknesses
of connecting lines indicating relative strength of the relationships.
The technology also allows users to infer and reason across
the graph, and to create pattern-based queries containing, for
instance,
signatures for a specific biological function (such as biomarkers used as
disease profile for a certain stage of a disease or a certain
demographic
patient group with a specific genetic profile).
"With the ever-growing Linked Open
Data (LOD) in semantic
format, IO's technology provides tools to build and enrich knowledge bases for
specific user needs—such as liver toxicity
categorization, comparative
effectiveness of cancer treatments, risk assessment of organ transplant
failures or differentiation of stable versus
ruptured plaques in cardiac
diseases, which are all cases where IO has applied its technologies in the
past. This way, knowledge is never stale; it can
keep pace with scientific
advances, and is actually actionable—you can use it as decision support in
screening and diagnostic or therapeutic
applications," Gombocz says.
Currently, there are about 45 public databases in use by IO
that
contain information on organisms, pathogens, genes and proteins.
"One application of this novel
approach is to identify
peptides from different microorganisms with a common mechanism of actions, and
to categorize them as potential biomarkers, and
it also has the capability to
detect microbial threats prior to onset of disease symptoms," says Ali Pervez,
vice president of marketing at Sage-N
Research.
"Future applications of this technology will enable
automated screening for biological
threats, to characterize origin and type of
disease and to develop preventive measures (drugs or vaccines) effective for
several classes of
microorganism," adds Robert Stanley, president of IO.
"Together with IO's semantic knowledge base
concept,
Sage-N's Sorcerer and IO's Sentient Knowledge Explorer and Sentient WebQuery
allow us to pre-package entire knowledge bases of biological
systems through meaningful
interconnection of experimental and public data resources under a common
architectural framework," Gombocz notes. "The
partnership has been a logical
synergistic extension of capabilities through combination of innovation from
both sides. IO Informatics, together with
its collaborators and customers, has
been instrumental in the arena of biomarker discovery and qualification, and
Sage-N has been leading in spectra-
based ID research for microbial pathogens.
The partnership extends the efforts towards a deeper understanding of peptide-
and protein-related
mechanistic impact on disease-related pathways based on
systems biological network views—all areas which require expertise in
high-throughput
workflows, scalability and dynamic knowledge building towards
real-time actionable applications which account for alerting and decision
support via web
and mobile platforms."
Sage-N teams with Pressure
BioSciences on
analysis of cell membrane proteins
SOUTH EASTON, Mass.—Sage-N Research Inc. also
announced
March 19 that it will collaborate with Pressure
BioSciences Inc. (PBI) to
develop software applications on Sage-N's SORCERER Integrated Data Appliance
platform. The new software will be designed
to work with PBI's patented and
enabling pressure cycling technology (PCT) system, a technology platform that
is used to extract, among other
biomolecules, integral cell membrane and other
proteins for subsequent mass spectrometry analysis.
According to the companies, these proteins are of significant
clinical importance due to their roles in cell signal transduction in cancer,
membrane transport disorders like Crohn's disease, pathogen invasion such as
HIV and their roles in other diseases and disorders. Unfortunately,
integral
cell membrane proteins are traditionally very difficult to extract. In some
cases, harsh chemicals are used in the extraction process, causing
such severe
protein degradation that subsequent proteomic analysis is compromised.
PBI's PCT
platform uses rapid cycles of low and ultra-high
pressure to safely and effectively extract proteins from samples (including
cell membranes) that are
suitable for analysis by analytical methods such as
mass spectrometry. The PCT platform also provides a high level of automation,
speed and
reproducibility in the enzymatic breakdown of proteins. This allows
the PCT-enhanced digestion to be completed in under an hour, compared to the
standard four to 12 hours, according to PBI.
Sage-N's SORCERER Integrated Data Appliance platform
provides complementary software applications that are customized for each
particular sample preparation chemistry. This results in a semi-automated
system for membrane and other protein analysis that can use any modern tandem
mass spectrometer and liquid chromatography system, says Sage-N.
"We plan to seamlessly integrate PBI's front-end PCT Sample
Preparation System—instruments and
consumables—with Sage-N's SORCERER back-end
data reduction software," explains Richard T. Schumacher, president and CEO of
PBI. "We expect to offer
this bundled platform as an option to stand-alone
sample preparation and data reduction methods used currently by the mass
spectrometry laboratory. We
believe that by bundling these enabling platforms,
we will be offering a higher quality, more efficient and less costly solution
than they currently
have for sample preparation and data reduction. Since the
companies now target an identical market—the mass spectrometry laboratory—we
expect to share
a number of marketing and selling programs directed at this
market going forward. Overall, we believe our new co-marketing program will
reduce costs
and increase sales for both PBI and Sage-N before the end of
2012."
Code: E041212 Back |
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