Persistent Topology of Protein Space
Publikation: Bidrag til bog/antologi/rapport › Bidrag til bog/antologi › Forskning › fagfællebedømt
Protein fold classification is a classic problem in structural biology and bioinformatics. We approach this problem using persistent homology. In particular, we use alpha shape filtrations to compare a topological representation of the data with a different representation that makes use of knot-theoretic ideas. We use the statistical method of Angle-based Joint and Individual Variation Explained (AJIVE) to understand similarities and differences between these representations.
Originalsprog | Engelsk |
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Titel | Research in Computational Topology 2 |
Forlag | Springer |
Publikationsdato | 2022 |
Sider | 223-244 |
ISBN (Trykt) | 978-3-030-95518-2 |
ISBN (Elektronisk) | 978-3-030-95519-9 |
DOI | |
Status | Udgivet - 2022 |
Navn | Association for Women in Mathematics Series |
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Vol/bind | 30 |
ISSN | 2364-5733 |
Bibliografisk note
Funding Information:
Acknowledgments Peter Røgen provided helpful comments and suggestions regarding the GIT vector discussion. We also thank the anonymous reviewers for substantial comments and suggestions. The research of J. E. Borgert and J. S. Marron were partially supported by the grants NIH/NIAMS, P30AR072580 and NIH/NIH, R21AR074685.
Publisher Copyright:
© 2022, The Author(s) and the Association for Women in Mathematics.
ID: 309122829