GAP creates a consensus pattern from a set of scanned gels, eliminating the unavoidable variations between scans caused by the following factors:
Subsequently, this consensus pattern can be used to test particular scans for conformation to the standard, and to perform peak identification and integration. The algorithms are completely peak-independent, allowing automated alignment and comparison of highly complicated patterns individually or as a batch process. Furthermore, no user intervention is required to identify peaks to be matched (Figure 2).
GAP was developed by a team of PhD’s in Biochemistry, Applied Math, and Computer Science to be accurate yet fast. It is already used by leading biotechnology firms in quality control situations where the adherence of a pattern to a standard must be tested prior to release.
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