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Article

Touring protein space with matt

Authors:

Matt MenkeAuthors Info & Claims

ISBRA'10: Proceedings of the 6th international conference on Bioinformatics Research and Applications

Pages 18 - 28

https://doi.org/10.1007/978-3-642-13078-6_4

Published: 23 May 2010 Publication History

Abstract

Using the Matt structure alignment program, we take a tour of protein space, producing a hierarchical clustering scheme that divides protein structural domains into clusters based on geometric dissimilarity. While it was known that purely structural, geometric, distance-based metrics of structural similarity, such as Dali/FSSP, could largely replicate hand-curated schemes such as SCOP at the family level, it was an open question as to whether any such scheme could approximate SCOP at the more distant superfamily and fold levels. We partially answer this question in the affirmative, by designing a clustering scheme based on Matt that approximately matches SCOP at the superfamily level. Implications for the debate over the organization of protein fold space are discussed.

References

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Digital Library

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Cited By

Daniels NGallant ARamsey NCowen L(2015)MRFyIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2014.234468212:1(4-16)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1109/TCBB.2014.2344682
Daniels NKumar ACowen LMenke M(2012)Touring Protein Space with MattIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2011.709:1(286-293)Online publication date: 1-Jan-2012
https://dl.acm.org/doi/10.1109/TCBB.2011.70
Nadimpalli SDaniels NCowen LGrossman RRzhetsky AKim SWang W(2011)FormattProceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine10.1145/2147805.2147842(315-319)Online publication date: 1-Aug-2011
https://dl.acm.org/doi/10.1145/2147805.2147842

Touring protein space with matt
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning

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Information & Contributors

Information

Published In

cover image Guide Proceedings

ISBRA'10: Proceedings of the 6th international conference on Bioinformatics Research and Applications

May 2010

253 pages

ISBN:3642130771

Editors:
Mark Borodovsky
School of Biology, Department of Biomedical Engineering and College of Computing, Georgia Institute of Technology, Atlanta, Georgia
,
Johann Peter Gogarten
Molecular and Cell Biology Department, University of Connecticut, 91 North Eagleville Road, Unit 3125, Storrs, CT
,
Teresa M. Przytycka
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Building 38A 8S814, Bethesda, MD
,
Sanguthevar Rajasekaran
Department of Computer Science and Engineering, University of Connecticut, 257 ITE Building, 371 Fairfield Way, Storrs, CT

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 23 May 2010

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Cited By

Daniels NGallant ARamsey NCowen L(2015)MRFyIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2014.234468212:1(4-16)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1109/TCBB.2014.2344682
Daniels NKumar ACowen LMenke M(2012)Touring Protein Space with MattIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2011.709:1(286-293)Online publication date: 1-Jan-2012
https://dl.acm.org/doi/10.1109/TCBB.2011.70
Nadimpalli SDaniels NCowen LGrossman RRzhetsky AKim SWang W(2011)FormattProceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine10.1145/2147805.2147842(315-319)Online publication date: 1-Aug-2011
https://dl.acm.org/doi/10.1145/2147805.2147842

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