Multispectral imaging bridges the gap between ‘omics’ multiplexed array-based techniques and conventional tissue imaging. This webinar provides an overview of how leading scientists are using multi-label imaging in combination with pattern-recognition image analysis software to analyze biomarkers specific to important disease-related cellular states, such as signaling configuration, stem cell pluripotency, and receptor expression.  Call +1-781-935-9099 ext 158 or e-mail us NOW at toleary@cri-inc.com to sign up for this FREE webinar.

Featured Speaker: James Mansfield
Director, Multispectral Imaging Systems
Cambridge Research & Instrumentation, Inc.
Title: Quantitating multiple protein expressions in intact tissue.
Date: Thursday, June 17, 2010
Time: 1:00 PM - 2:00 PM EDT
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CRi technology helps to bridge the gap between advances made in the ‘omics’ multiplexed array-based techniques and conventional tissue imaging. This webinar provides an overview of how leading scientists are using multi-label imaging in intact tissue, in combination with pattern-recognition image analysis software to analyze biomarkers specific to important disease-related cellular states, such as signaling configuration, stem cell pluripotency, and receptor expression.  

Improved specificity in determining disease subclasses through protein expression profiles is a goal of many studies. Obtaining this specific information requires the analysis of multiple proteins on a per-cell basis in intact tissues, from specific architectural contexts.

In pharmaceutical drug development, revealing correlations between protein activity and clinical outcome supports target validation, trial design, patient selection, response assessment, and, if trials are successful, the diagnostic component of theranostics. However, the ability of tools to support these activities depends strongly on their precision and accuracy for quantitating protein labels. Multispectral imaging coupled with automated learn-by-example analysis software offer a powerful combination to generate reproducible data of per-cell phenotypes in tumor regions or other regions of interest. Many techniques deployed today, such as those based on microarray detection, or analysis of sample lysates, provide data that are, in fact, averages from volumes of tissue, including many cells not of interest. These methods blur-out key proteomic information that resides at the cellular level and that relates to the signaling states of individual cells.

System Requirements
PC-based attendees
Required: Windows® 7, Vista, XP, 2003 Server or 2000
Macintosh®-based attendees
Required: Mac OS® X 10.4.11 (Tiger®) or newer

Space is limited.
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