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About TranscriptoNET ... |
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TranscriptoNET is an open-access, online resource developed by Kinexus Bioinformatics
Corporation to foster systems proteomics research in academia and industry. It features
comprehensive information on the mRNA expression levels of about 20,000 genes in
about 600 types of human organs, tissues and cells as measured with gene microarrays.
The original data used in TranscriptoNET was retrieved from the National Center
for Biotechnology Information Gene Expression Omnibus (NCBI GEO), which serves as
a repository of experimental gene microarray results submitted by diverse academic
and industrial laboratories around the world. With the aid of our academic collaborators,
Kinexus has normalized the data from over 900 different studies with over 6000 biological
specimens to permit investigations of gene expression and potential interactions
that can only be undertaken with such a large dataset of over 125,000,000 gene expression
measurements. This normalization process was based on the identification of 60 genes
that were commonly and highly expressed in all of the biological samples.
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In the selection of human specimens for inclusion in TranscriptoNET, we have paid
special interest to human tumours and cancer cell lines to identify the differential
regulation of genes in cancer. We believe that this can uncover new potential oncogenes
and tumour suppressor genes that may encode cancer protein biomarkers and drug targets.
We invite the biomedical research community to use TranscriptoNET as a powerful
tool for discovery of genes that are uniquely or commonly expressed throughout the
human body, and to uncover possible functional interactions amongst the 20,000 proteins
encoded by the human genome based on their co-expression patterns. The differential
expression of genes determines the structures and biochemical activities in cells
that define their physiological functions. TranscriptoNET could also be used to
aid researchers in understanding how the body’s diverse organs, tissues and cells
may be developmentally related.
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Instructions ...
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TranscriptoNET is designed to be fast and simple to navigate. Presently, there are
8 different types of queries that you can perform with TranscriptoNET. You can search
for target gene or protein if you know its UniProt ID, RefSeq or International Protein
Identification codes or one of its common alias names. A list of possible options
for genes/proteins are generated by typing at least three letters of their name
or identification number, and waiting for a few seconds for a complete list to appear.
The optimum web browsers for using TranscriptoNET are Internet Explorer, Firefox
and Safari.
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Other Useful Online Resources From Kinexus ...
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Other Useful Online Resources From Kinexus … TranscriptoNET, and its companion websites
PhosphoNET and KinaseNET are the first of several planned on-line knowledgebases
that will become available from Kinexus Bioinformatics Corporation as part of our
SigNET KnowledgeBank in Kinetica Online to accelerate signal transduction research.
Additional knowledgebases are in development for human protein phosphatases, adapter,
stress proteins and transcription factors. For semi-quantitative data on actual
protein expression in over 10,000 diverse biological specimens, please also visit
our open-access KiNET DataBank with immunoblotting and antibody microarray analyses
with over 800 pan- and phosphosite-specific antibodies.
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Funding and Advertising Opportunities ...
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To develop and sustain this free resource, we are seeking sponsorship from foundations
and corporations. We gratefully acknowledge
financial assistance for TranscriptoNET from the National Research Council of
Canada Industrial Assistance Program and the Natural Sciences and Engineering
Research Council of Canada. It is possible for
commercial vendors of signal transduction reagents and services to advertise their
relevant products and services on this site. Interested parties should contact our
Sales and Marketing Department at info@kinexus.ca or call toll free in North America
1-866-KINEXUS.
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Copyright 2019 Kinexus Bioinformatics Corporation
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