IDEAS home Printed from https://ideas.repec.org/a/spr/advdac/v7y2013i2p147-179.html
   My bibliography  Save this article

Fuzzy spectral clustering by PCCA+: application to Markov state models and data classification

Author

Listed:
  • Susanna Röblitz
  • Marcus Weber

Abstract

Given a row-stochastic matrix describing pairwise similarities between data objects, spectral clustering makes use of the eigenvectors of this matrix to perform dimensionality reduction for clustering in fewer dimensions. One example from this class of algorithms is the Robust Perron Cluster Analysis (PCCA+), which delivers a fuzzy clustering. Originally developed for clustering the state space of Markov chains, the method became popular as a versatile tool for general data classification problems. The robustness of PCCA+, however, cannot be explained by previous perturbation results, because the matrices in typical applications do not comply with the two main requirements: reversibility and nearly decomposability. We therefore demonstrate in this paper that PCCA+ always delivers an optimal fuzzy clustering for nearly uncoupled, not necessarily reversible, Markov chains with transition states. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Susanna Röblitz & Marcus Weber, 2013. "Fuzzy spectral clustering by PCCA+: application to Markov state models and data classification," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 7(2), pages 147-179, June.
  • Handle: RePEc:spr:advdac:v:7:y:2013:i:2:p:147-179
    DOI: 10.1007/s11634-013-0134-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11634-013-0134-6
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11634-013-0134-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mingyu Li & Xiaobing Lan & Xinchao Shi & Chunhao Zhu & Xun Lu & Jun Pu & Shaoyong Lu & Jian Zhang, 2024. "Delineating the stepwise millisecond allosteric activation mechanism of the class C GPCR dimer mGlu5," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Kalyan S. Chakrabarti & Simon Olsson & Supriya Pratihar & Karin Giller & Kerstin Overkamp & Ko On Lee & Vytautas Gapsys & Kyoung-Seok Ryu & Bert L. Groot & Frank Noé & Stefan Becker & Donghan Lee & Th, 2022. "A litmus test for classifying recognition mechanisms of transiently binding proteins," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    3. Ritaban Halder & Daniel A. Nissley & Ian Sitarik & Yang Jiang & Yiyun Rao & Quyen V. Vu & Mai Suan Li & Justin Pritchard & Edward P. O’Brien, 2023. "How soluble misfolded proteins bypass chaperones at the molecular level," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    4. Daniel A. Nissley & Yang Jiang & Fabio Trovato & Ian Sitarik & Karthik B. Narayan & Philip To & Yingzi Xia & Stephen D. Fried & Edward P. O’Brien, 2022. "Universal protein misfolding intermediates can bypass the proteostasis network and remain soluble and less functional," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    5. Gregory M. Martin & Monica L. Fernández-Quintero & Wen-Hsin Lee & Tossapol Pholcharee & Lisa Eshun-Wilson & Klaus R. Liedl & Marie Pancera & Robert A. Seder & Ian A. Wilson & Andrew B. Ward, 2023. "Structural basis of epitope selectivity and potent protection from malaria by PfCSP antibody L9," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    6. Lin, Yanwen & Hao, Yongchao & Shi, Qiao & Xu, Yihua & Song, Zixuan & Zhou, Ziyue & Fu, Yuequn & Zhang, Zhisen & Wu, Jianyang, 2024. "Enhanced formation of methane hydrates via graphene oxide: Machine learning insights from molecular dynamics simulations," Energy, Elsevier, vol. 289(C).
    7. Yuxuan Zhuang & Rebecca J. Howard & Erik Lindahl, 2024. "Symmetry-adapted Markov state models of closing, opening, and desensitizing in α 7 nicotinic acetylcholine receptors," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    8. Ravi Kumar Verma & Ara M Abramyan & Mayako Michino & R Benjamin Free & David R Sibley & Jonathan A Javitch & J Robert Lane & Lei Shi, 2018. "The E2.65A mutation disrupts dynamic binding poses of SB269652 at the dopamine D2 and D3 receptors," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-18, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:advdac:v:7:y:2013:i:2:p:147-179. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.