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| Marc Fasnacht, Columbia University |
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| Marc Fasnacht earned his diploma in physics from the Swiss Federal Institute of Technology in Lausanne, Switzerland and his Ph.D. from Carnegie Mellon University in Pittsburgh, where he worked with Dr. Robert H. Swendsen and Dr. John M. Rosenberg. His graduate research focused on developing efficient simulation methods for physical and biological systems. While at Carnegie Mellon, Dr. Fasnacht also earned a MS degree in knowledge discovery and data mining. He is currently a postdoctoral researcher in Dr. Barry Honig's group at HHMI at Columbia University where he is working on computational methods for protein structure prediction.
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Automated Methods for identifying Structural Motifs: Helix Couples in the Globins
Marc Fasnacht, Columbia University
A lot of work has gone into predicting the secondary (small scale) structure of proteins from their amino acid sequence. Current research indicates that there are limits on how well secondary structure can be predicted from local sequence information. To further advance prediction, the interactions between elements of secondary structure which are inherently non-local, have to be better understood.
This project studies a special case of secondary structure interaction, coupled helical motifs, consisting of two interacting helices. The underlying hypothesis of this work is that there are different types of coupled helical motifs, which can be characterized by different sets of rules governing the underlying amino acid sequence of the protein. In order to learn such rules, a classification of the coupled helical motifs needs to be introduced. This can be achieved by unsupervised learning methods such as clustering. We present a method to automatically extract structural motifs in proteins. The method uses hierarchical agglomerative clustering to find structurally equivalent sets of motifs in proteins. These motifs can be used for study of the underlying amino acid sequence. We test the method on a set of coupled helical motifs from the globin family of proteins. It rediscovers important aspects of the well known structural hierarchy of this protein family.
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