Signal peptide prediction
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Tony Smith introduces signal peptide prediction, an application of data mining to a problem in bioinformatics. A sequence of amino acids that makes up a protein begins with an initial portion of 20 or 30 amino acids called the “signal peptide” that unlocks a membrane for the protein to pass through. The problem is to determine the “cleavage point” where the signal peptide ends. An important question is whether we seek an accurate prediction or an explanatory model. One potentially useful feature is the length of the signal peptide; another is the amino acids immediately upstream and immediately downstream of the cleavage point. Overfitting is a problem, and domain knowledge from experts is an important ingredient for success – data mining is a collaborative process.
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Advanced Data Mining with Weka
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