For a project, I want to predict the subcellular localization of some proteins. I am a student in software Informatics at the University of applied Science HEIG-VD.
Subcellular localization prediction is a common problem in the bioinformatics, but I have a problem
With the data I found. In this database: of human and mouse proteins, we can see that there are more than 30 different localizations.
At my level, and for the use of my exercise, 30 classes to predict is too much.
Where can I find a mapping to reduce those 30 classes to 4 or 5?
I tried QuickGO, to see the ancestor tree of the different classes, but nothing conclusive. Somebody might have done that, but I lack knowledge on bioinformatic web research.
There are the classes I wanted to map to reduce the number of classes :
- Cytoplasm (GO:0005737)
- Cytoplasmic Vesicles (GO:0016023)
- Endoplasmic Reticulum (GO:0005783)
- Endosomes (GO:0005768)
- Extracellular (GO:0005576)
- Golgi Apparatus (GO:0005794)
- Lipid Particles (GO:0005811)
- Lysosomes (GO:0005764)
- Melanosome (GO:0042470)
- Mitochondria (GO:0005739)
- Nucleus (GO:0005634)
- Peroxisome (GO:0005777)
- Plasma Membrane (GO:0005886)
- Synaptic Vesicles (GO:0008021)
- Cellular Component Unknown (GO:0008372)
- Apical Plasma Membrane (GO:0016324)
- Basolateral Plasma Membrane (GO:0016323)
- Centrosome (GO:0005813)
- Golgi Cis Cisterna (GO:0000137)
- Cytoskeleton (GO:0005856)
- Early Endosomes (GO:0005769)
- ERGIC (GO:0005793)
- Inner Mitochondrial Membrane (GO:0005743)
- Late Endosomes (GO:0005770)
- Medial-Golgi (GO:0005797)
- Outer Mitochondrial Membrane (GO:0005741)
- Secretory Granule (GO:0030141)
- Golgi Trans Cisterna (GO:0000137)
- Golgi Trans Face (GO:0005802)
- Tight Junction (GO:0005923)
- Transport Vesicle (GO:0030133)