Luis Pedro Coelho, Joshua D. Kangas, Armaghan Naik, Elvira Osuna-Highley, Estelle Glory-Afshar, Margaret Fuhrman, Ramanuja Simha, Peter B. Berget, Jonathan W. Jarvik, and Robert F. Murphy, Determining the subcellular location of new proteins from microscope images using local features in Bioinformatics, 2013 [DOI]
I will have a series of blog posts on all the ideas on this paper. This first one will have the background to the work.
Here is a cartoon view of a eukariotic cell, taken from Wikipedia.
It has several organelles: the nucleus, the Golgi apparatus, the endoplasmic reticulum (ER), &c Proteins will travel to their assigned locations to perform their tasks.
We would like to know where proteins locate. The best way to do so conclusively is to somehow image the protein in cells, which we can do with fluorescent microscopy. The image below is exactly the result of one such experiment. In green, we see a protein which has been tagged with GFP (see below for technical details). In red, we see a nuclear marker (thus you can recognize this a a nucleolar protein).
The subcellular location determination problem is to go from image such as these to location assignments. It is done using pattern recognition.
Technical details: The image above is of NIH 3T3 cells where proteins have been tagged (using CD tagging) to generate cell lines where proteins are now chimeric and contain a GFP cassette.
- New Paper: Determining the subcellular location of new proteins from microscope images using local features (metarabbit.wordpress.com)
- Paper Review: Unsupervised Clustering of Subcellular Protein Expression Patterns in High-Throughput Microscopy Images Reveals Protein Complexes and Functional Relationships between Proteins (metarabbit.wordpress.com)