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MolSignTM
The MolSignTM database can be used to
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Identify drug targets associated with a
disease
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To analyze disease proteomics, genomics or
Metabolomics.
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Study the effects of marker in disease
(Disease progression, risk stratification) or
clinical setting (patient prognosis, drug
response prediction).
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Compare diseased and normal states
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Discover modifications affecting a disease
pathology
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Understand the expression profiles of specific
molecules
Product Profile
The MolSignTM database is a comprehensive
collection of potential disease marker
information from literature and peer reviewed
articles (1998 onwards).
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Data from more than 4200 research
articles
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9000 potential biomarkers spanning
three major disease areas
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Neoplasm: 8600 markers across
different neoplasms
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Arthritis: 1000 markers across
rheumatoid, juvenile and osteoarthritis
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Diabetes: 540 markers covering type I
and II diabetes
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Over 85,000 records and updated every
quarter.
Key Functionality
The MolSignTM database is manually curated and
quality checked, having information from over
4000 articles covering
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Expression studies: Gene/Protein
expression, metabolomics
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Mutation: Polymorphism,
chromosomal aberrations, including loss of
heterozygosity and microsatellite instability
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Epigenetic changes, splicing
events and post-translational
modifications
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Effects of inhibitors and drugs on the markers
Biomolecules covered include genes & splice
variants, proteins & isoforms, metabolites,
microRNA and autoantibodies.
Strict adherence to standard nomenclature and
controlled vocabulary makes it easy to search.
The database can be queried directly by marker,
disease and can be combined with any of the
other fields available through the interface.
The reports are conveniently linked to 17 public
domain databases.
Modules
Disease Profiler
DiseaseProfiler is a statistical tool to
determine the significance of a marker in a
disease. The tool uses data from MolSign to
determine a statistical framework for the
correlation of markers to diseases.
Important parameters from the MolSign database
are chosen as variables for assigning weights
for the biomarker, and the weight values are
used for likelihood calculations. The
specificity of each marker to a particular
disease is calculated by the one-tailed test.
The DiseaseProfiler can be used:
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To identify markers that have been up or down
regulated in a particular disease.
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To validate microarray data.
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To identify disease specific biomarkers.
Clinical Trial Database-
This module captures information on both
currently active and published literature on
biomarker-oriented clinical trials. The main
focus is on ongoing clinical trials from various
national Clinical Trials Registries,
wherein data is captured on surrogate
biomarkers, biochemical, pharmacogenomics, and
imaging biomarkers.
A target-centric focus is taken up for
these clinical biomarkers, and data mapping is
provided at the pre-clinical, qualification
and exploratory levels. Parallel data is
thus obtained for potential markers for future
use.
The Clinical Trial Database can be used to:
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Identify current trends in biomarker-oriented
clinical trials
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Obtain information on new or modified drug
treatment regimens
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Identify potential biomarkers that can
be used as surrogate endpoints
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Know the predictive/prognostic status of a
biomarker in the clinical setting
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