What is it about?
Building machine learning systems to classify protein sequences into their likely sub-cellular location. This involves identifying the particular sequence motifs that are used by transport proteins to move them to the location. Technically we use a combination of neural networks and support vector machines, the neural networks learn potential feature vectors and then the support vector machine performs the final classification.
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This page is a summary of: DETECTING AND SORTING TARGETING PEPTIDES WITH NEURAL NETWORKS AND SUPPORT VECTOR MACHINES, Journal of Bioinformatics and Computational Biology, February 2006, World Scientific Pub Co Pte Lt,
DOI: 10.1142/s0219720006001771.
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