Literature DB >> 24336411

A combinatorial approach to graphlet counting.

Tomaž Hočevar1, Janez Demšar.   

Abstract

MOTIVATION: Small-induced subgraphs called graphlets are emerging as a possible tool for exploration of global and local structure of networks and for analysis of roles of individual nodes. One of the obstacles to their wider use is the computational complexity of algorithms for their discovery and counting.
RESULTS: We propose a new combinatorial method for counting graphlets and orbit signatures of network nodes. The algorithm builds a system of equations that connect counts of orbits from graphlets with up to five nodes, which allows to compute all orbit counts by enumerating just a single one. This reduces its practical time complexity in sparse graphs by an order of magnitude as compared with the existing pure enumeration-based algorithms.
AVAILABILITY AND IMPLEMENTATION: Source code is available freely at http://www.biolab.si/supp/orca/orca.html.

Mesh:

Substances:

Year:  2013        PMID: 24336411     DOI: 10.1093/bioinformatics/btt717

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  22 in total

1.  From homogeneous to heterogeneous network alignment via colored graphlets.

Authors:  Shawn Gu; John Johnson; Fazle E Faisal; Tijana Milenković
Journal:  Sci Rep       Date:  2018-08-21       Impact factor: 4.379

2.  Identification of caveolin-1 domain signatures via machine learning and graphlet analysis of single-molecule super-resolution data.

Authors:  Ismail M Khater; Fanrui Meng; Ivan Robert Nabi; Ghassan Hamarneh
Journal:  Bioinformatics       Date:  2019-09-15       Impact factor: 6.937

3.  Combinatorial algorithm for counting small induced graphs and orbits.

Authors:  Tomaž Hočevar; Janez Demšar
Journal:  PLoS One       Date:  2017-02-09       Impact factor: 3.240

4.  Graphlet signature-based scoring method to estimate protein-ligand binding affinity.

Authors:  Omkar Singh; Kunal Sawariya; Polamarasetty Aparoy
Journal:  R Soc Open Sci       Date:  2014-12-10       Impact factor: 2.963

5.  Proper evaluation of alignment-free network comparison methods.

Authors:  Ömer Nebil Yaveroğlu; Tijana Milenković; Nataša Pržulj
Journal:  Bioinformatics       Date:  2015-03-24       Impact factor: 6.937

6.  An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.

Authors:  Ine Melckenbeeck; Pieter Audenaert; Tom Michoel; Didier Colle; Mario Pickavet
Journal:  PLoS One       Date:  2016-01-21       Impact factor: 3.240

7.  Exploring the structure and function of temporal networks with dynamic graphlets.

Authors:  Y Hulovatyy; H Chen; T Milenković
Journal:  Bioinformatics       Date:  2015-06-15       Impact factor: 6.937

8.  Integrated interactions database: tissue-specific view of the human and model organism interactomes.

Authors:  Max Kotlyar; Chiara Pastrello; Nicholas Sheahan; Igor Jurisica
Journal:  Nucleic Acids Res       Date:  2015-10-29       Impact factor: 16.971

9.  Alignment of dynamic networks.

Authors:  V Vijayan; D Critchlow; T Milenkovic
Journal:  Bioinformatics       Date:  2017-07-15       Impact factor: 6.937

10.  Alignment-free protein interaction network comparison.

Authors:  Waqar Ali; Tiago Rito; Gesine Reinert; Fengzhu Sun; Charlotte M Deane
Journal:  Bioinformatics       Date:  2014-09-01       Impact factor: 6.937

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.