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Structural Discrimination of Networks by Using Distance, Degree and Eigenvalue-Based Measures (Structural Discrimination of Networks)

Dehmer, Matthias ; Grabner, Martin ; Furtula, Boris; Gomez-gardenes, Jesus (Editor)

PLoS ONE, 2012, Vol.7(7), p.e38564 [Tạp chí có phản biện]

E-ISSN: 1932-6203 ; DOI: 10.1371/journal.pone.0038564

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  • Nhan đề:
    Structural Discrimination of Networks by Using Distance, Degree and Eigenvalue-Based Measures (Structural Discrimination of Networks)
  • Tác giả: Dehmer, Matthias ; Grabner, Martin ; Furtula, Boris
  • Gomez-gardenes, Jesus (Editor)
  • Chủ đề: Research Article ; Biology ; Chemistry ; Computer Science ; Mathematics ; Chemistry ; Computational Biology ; Computer Science ; Mathematics
  • Là 1 phần của: PLoS ONE, 2012, Vol.7(7), p.e38564
  • Mô tả: In chemistry and computational biology, structural graph descriptors have been proven essential for characterizing the structure of chemical and biological networks. It has also been demonstrated that they are useful to derive empirical models for structure-oriented drug design. However, from a more general (complex network-oriented) point of view, investigating mathematical properties of structural descriptors, such as their uniqueness and structural interpretation, is also important for an in-depth understanding of the underlying methods. In this paper, we emphasize the evaluation of the uniqueness of distance, degree and eigenvalue-based measures. Among these are measures that have been recently investigated extensively. We report numerical results using chemical and exhaustively generated graphs and also investigate correlations between the measures.
  • Ngôn ngữ: English
  • Số nhận dạng: E-ISSN: 1932-6203 ; DOI: 10.1371/journal.pone.0038564

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