Automatic Segmentation of Proteomic Images - Robotics Institute Carnegie Mellon University
Automatic Segmentation of Proteomic Images
Project Head: Fernando De la Torre Frade

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.

past staff

  • Esteban Curras
  • Jonathan S. Minden