NETWORK INFERENCE from COMPLEX SYSTEMS STEADY STATES OBSERVATIONS: THEORY and METHODS

Hoi To Wai; Anna Scaglione; Baruch Barzel; Amir Leshem

doi:10.1109/DSW.2018.8439896

NETWORK INFERENCE from COMPLEX SYSTEMS STEADY STATES OBSERVATIONS: THEORY and METHODS

Hoi To Wai, Anna Scaglione, Baruch Barzel, Amir Leshem

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents new results on network inference from observations of steady state behaviors emerging from perturbations of complex networks dynamics. We focus on the estimation of network and flow parameters using a general regularized inference formulation, which is tackled numerically using the standard technique of alternating optimization. We argue that relying only on the steady states equations removes the requirement of precisely recording transient data, and allows to meaningfully combine data from multiple experiments. To provide theoretical benchmarks we study the relationship between topological and functional characteristics of the system and the divergence between the steady state behavior observed, to give rigorous performance benchmarks. Numerical results are presented on examples with social networks and gene regulatory networks to justify our claims.

Original language	English
Title of host publication	2018 IEEE Data Science Workshop, DSW 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	155-159
Number of pages	5
ISBN (Print)	9781538644102
DOIs	https://doi.org/10.1109/DSW.2018.8439896
State	Published - 17 Aug 2018
Externally published	Yes
Event	2018 IEEE Data Science Workshop, DSW 2018 - Lausanne, Switzerland Duration: 4 Jun 2018 → 6 Jun 2018

Publication series

Name	2018 IEEE Data Science Workshop, DSW 2018 - Proceedings

Conference

Conference	2018 IEEE Data Science Workshop, DSW 2018
Country/Territory	Switzerland
City	Lausanne
Period	4/06/18 → 6/06/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

complex network systems
gene networks
network identifiability
network inference
social networks

Access to Document

10.1109/DSW.2018.8439896

Cite this

Wai, H. T., Scaglione, A., Barzel, B., & Leshem, A. (2018). NETWORK INFERENCE from COMPLEX SYSTEMS STEADY STATES OBSERVATIONS: THEORY and METHODS. In 2018 IEEE Data Science Workshop, DSW 2018 - Proceedings (pp. 155-159). Article 8439896 (2018 IEEE Data Science Workshop, DSW 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DSW.2018.8439896

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abstract = "This paper presents new results on network inference from observations of steady state behaviors emerging from perturbations of complex networks dynamics. We focus on the estimation of network and flow parameters using a general regularized inference formulation, which is tackled numerically using the standard technique of alternating optimization. We argue that relying only on the steady states equations removes the requirement of precisely recording transient data, and allows to meaningfully combine data from multiple experiments. To provide theoretical benchmarks we study the relationship between topological and functional characteristics of the system and the divergence between the steady state behavior observed, to give rigorous performance benchmarks. Numerical results are presented on examples with social networks and gene regulatory networks to justify our claims.",

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year = "2018",

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doi = "10.1109/DSW.2018.8439896",

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Wai, HT, Scaglione, A, Barzel, B & Leshem, A 2018, NETWORK INFERENCE from COMPLEX SYSTEMS STEADY STATES OBSERVATIONS: THEORY and METHODS. in 2018 IEEE Data Science Workshop, DSW 2018 - Proceedings., 8439896, 2018 IEEE Data Science Workshop, DSW 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 155-159, 2018 IEEE Data Science Workshop, DSW 2018, Lausanne, Switzerland, 4/06/18. https://doi.org/10.1109/DSW.2018.8439896

NETWORK INFERENCE from COMPLEX SYSTEMS STEADY STATES OBSERVATIONS: THEORY and METHODS. / Wai, Hoi To; Scaglione, Anna; Barzel, Baruch et al.
2018 IEEE Data Science Workshop, DSW 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 155-159 8439896 (2018 IEEE Data Science Workshop, DSW 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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NETWORK INFERENCE from COMPLEX SYSTEMS STEADY STATES OBSERVATIONS: THEORY and METHODS

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