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Seminar with Mikael BodenTitle: Protein traffic control Speaker: Mikael Boden Time: 12-May, 11:00am Place: Room 78-621/622 The cell is a decentralised but still carefully controlled device, shuttling gene products, like proteins, through various compartments where they perform their functions. Mechanisms for this protein traffic control are not yet fully understood and machine learning techniques are being utilised to discover protein sequence signals that allow targeted drug design and the development of models that can be used to automatically annotate the growing number of sequences that are yet to be experimentally characterised. In relation to the current state-of-the-art, we report on improvements in accuracy for a range of models for predicting localisation of proteins -- making use of advanced machine learning techniques like recurrent neural networks and support vector machines. In particular we focus on the essential compartments and organelles, the secretory pathway, the mitochondrion, the chloroplast and the peroxisome. Our models are housed in the Protein Prowler, our online sequence prediction server, which has been endowed with graphical features allowing the user to scrutinize the outputs of the models. |
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