Literature DB >> 21639592

Networks for systems biology: conceptual connection of data and function.

F Emmert-Streib1, M Dehmer.   

Abstract

The purpose of this study is to survey the use of networks and network-based methods in systems biology. This study starts with an introduction to graph theory and basic measures allowing to quantify structural properties of networks. Then, the authors present important network classes and gene networks as well as methods for their analysis. In the last part of this study, the authors review approaches that aim at analysing the functional organisation of gene networks and the use of networks in medicine. In addition to this, the authors advocate networks as a systematic approach to general problems in systems biology, because networks are capable of assuming multiple roles that are very beneficial connecting experimental data with a functional interpretation in biological terms.

Mesh:

Year:  2011        PMID: 21639592     DOI: 10.1049/iet-syb.2010.0025

Source DB:  PubMed          Journal:  IET Syst Biol        ISSN: 1751-8849            Impact factor:   1.615


  40 in total

1.  PheNetic: network-based interpretation of molecular profiling data.

Authors:  Dries De Maeyer; Bram Weytjens; Joris Renkens; Luc De Raedt; Kathleen Marchal
Journal:  Nucleic Acids Res       Date:  2015-04-15       Impact factor: 16.971

2.  Direct estimation of differential networks.

Authors:  Sihai Dave Zhao; T Tony Cai; Hongzhe Li
Journal:  Biometrika       Date:  2014-06       Impact factor: 2.445

3.  Connections between classical and parametric network entropies.

Authors:  Matthias Dehmer; Abbe Mowshowitz; Frank Emmert-Streib
Journal:  PLoS One       Date:  2011-01-05       Impact factor: 3.240

4.  A Bayesian analysis of the chromosome architecture of human disorders by integrating reductionist data.

Authors:  Frank Emmert-Streib; Ricardo de Matos Simoes; Shailesh Tripathi; Galina V Glazko; Matthias Dehmer
Journal:  Sci Rep       Date:  2012-07-20       Impact factor: 4.379

5.  Structural properties and complexity of a new network class: Collatz step graphs.

Authors:  Frank Emmert-Streib
Journal:  PLoS One       Date:  2013-02-19       Impact factor: 3.240

6.  Integrative network biology: graph prototyping for co-expression cancer networks.

Authors:  Karl G Kugler; Laurin A J Mueller; Armin Graber; Matthias Dehmer
Journal:  PLoS One       Date:  2011-07-29       Impact factor: 3.240

7.  Organizational structure and the periphery of the gene regulatory network in B-cell lymphoma.

Authors:  Ricardo de Matos Simoes; Shailesh Tripathi; Frank Emmert-Streib
Journal:  BMC Syst Biol       Date:  2012-05-14

8.  Interfacing cellular networks of S. cerevisiae and E. coli: connecting dynamic and genetic information.

Authors:  Ricardo de Matos Simoes; Matthias Dehmer; Frank Emmert-Streib
Journal:  BMC Genomics       Date:  2013-05-11       Impact factor: 3.969

9.  RMol: a toolset for transforming SD/Molfile structure information into R objects.

Authors:  Martin Grabner; Kurt Varmuza; Matthias Dehmer
Journal:  Source Code Biol Med       Date:  2012-11-14

10.  Ensuring the statistical soundness of competitive gene set approaches: gene filtering and genome-scale coverage are essential.

Authors:  Shailesh Tripathi; Galina V Glazko; Frank Emmert-Streib
Journal:  Nucleic Acids Res       Date:  2013-02-06       Impact factor: 16.971

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