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Abstract: To study local structures in proteins, we previously developed an autoassociative artificial neural network (autoANN) and clustering tool to discover intrinsic features of macromolecular structures. The hidden unit activations computed by the trained autoANN are a convenient low-dimensional encoding of the local protein backbone structure. Clustering these activation vectors results in a unique classification of protein local structural features called Structural Building Blocks (SBBs). Here we ... (Update)
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BibTeX entry: (Update)
@misc{ fetrow-patterns,
author = "Jacquelyn S. Fetrow and Michael J. Palumbo and George Berg",
title = "Patterns, Structures, andAmino Acid Frequencies in Structural Building
Blocks, a Protein Secondary Structure Classification Scheme",
url = "citeseer.ist.psu.edu/470231.html" }
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