Bottom - Index of papers - Abstract - Paper as PDF - CUBIC
| Title: | Surface profiles predict sub-cellular localisation |
| Author: | Rajesh Nair & Burkhard Rost |
| Quote: | Preprint CUBIC_2001_05, Columbia University |
The gap between the number of known protein sequence and the knowledge about protein function is rapidly increasing. One important physical aspect of function is the sub-cellular localisation of a protein. Here, we trained two-layered feed-forward neural networks to predict the sub-cellular localisation for proteins of known structure. We introduced two novel key aspects: (1) using evolutionary information, and (2) using surface composition. We also trained networks only on the N-terms. Finally, we combined all our networks. We evaluated sustained levels of performance by four-fold cross-validation. The major single source of improvement was the use of evolutionary information. However, the com-bination of our various networks yielded the final, significant improvement over previous methods. The final system reached an accuracy above 80% (two-state). This level may suffice to make the method valuable for target selection in structural genomics.