A simplified approach to disulfide connectivity prediction from protein sequences |
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Authors: | Marc Vincent Andrea Passerini Matthieu Labbé Paolo Frasconi |
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Affiliation: | 1.Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica,Università degli Studi di Firenze,Firenze,Italy |
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Abstract: | Background Prediction of disulfide bridges from protein sequences is useful for characterizing structural and functional properties of proteins. Several methods based on different machine learning algorithms have been applied to solve this problem and public domain prediction services exist. These methods are however still potentially subject to significant improvements both in terms of prediction accuracy and overall architectural complexity. |
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