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Virginia Tech

Mathematical frameworks for quantitative network analysis

Abstract

dc:description.abstract

This thesis is comprised of three parts. The first part describes a novel framework for computing importance measures on graph vertices. The concept of a D-spectrum is introduced, based on vertex ranks within certain chains of nested sub-graphs. We show that the D- spectrum integrates the degree distribution and coreness information of the graph as two particular such chains. We prove that these spectra are realized as fixed points of certain monotone and contractive SDSs we call t-systems. Finally, we give a vertex deletion algorithm that efficiently computes D-spectra, and we illustrate their correlation with stochastic SIR-processes on real world networks. The second part deals with the topology of the intersection nerve for a bi-secondary structure, and its singular homology. A bi-secondary structure R, is a combinatorial object that can be viewed as a collection of cycles (loops) of certain at most tetravalent planar graphs. Bi-secondary structures arise naturally in the study of RNA riboswitches - molecules that have an MFE binary structural degeneracy. We prove that this loop nerve complex has a euclidean 3-space embedding characterized solely by H2(R), its second homology group. We show that this group is the only non-trivial one in the sequence and furthermore it is free abelian. The third part further describes the features of the loop nerve. We identify certain disjoint objects in the structure of R which we call crossing components (CC). These are non-trivial connected components of a graph that captures a particular non-planar embedding of R. We show that each CC contributes a unique generator to H2(R) and thus the total number of these crossing components in fact equals the rank of the second homology group.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Mathematics
Department dc:contributor.department
Mathematics
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Bura, Cotiso Andrei
Chair dc:contributor.committeechair
  • Reidys, Christian Michael
Committee members dc:contributor.committeemember
  • Orr, Daniel D.
  • Mortveit, Henning S.
  • Haskell, Peter E.

Subjects

dc:subject × 11

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:22413
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/95034

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Bura, Cotiso Andrei. Mathematical frameworks for quantitative network analysis. doctoral thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/95034