Carnegie Mellon University
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Automatic Segmentation of Proteomic Images
This project is no longer active.
Head: Fernando De la Torre Frade
Contact: Fernando De la Torre Frade
Mailing address:
Carnegie Mellon University
Robotics Institute
211 Smith Hall
Pittsburgh, PA 15213
Associated center(s) / consortia:
 Vision and Autonomous Systems Center (VASC)
Co-detecting spots on a cumulative proteomic image derived from two individual proteomic images (an in-gel image pair). Once the co-detection is done, the system quantifies spot protein abundance for each image and expresses these values as a ratio that indicates the changes in expression levels by direct comparison of corresponding spots. This ratio parameter can be used, in small-scale experiments, to directly evaluate changes between two labeled protein samples.