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Related Experiment Video

Updated: Jun 1, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Network inference using asynchronously updated kinetic Ising model.

Hong-Li Zeng1, Erik Aurell, Mikko Alava

  • 1Department of Applied Physics, Aalto University, FIN-00076 Aalto, Finland. hongli.zeng@tkk.fi

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|May 24, 2011
PubMed
Summary
This summary is machine-generated.

Network reconstruction from dynamical data is improved by Thouless-Anderson-Palmer (TAP) approximation over naive mean field (nMF). TAP shows better performance, especially at lower temperatures and with longer data lengths.

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Published on: September 8, 2023

Area of Science:

  • Statistical physics
  • Network science
  • Computational neuroscience

Background:

  • Reconstructing network structures from dynamical data is crucial for understanding complex systems.
  • Naive mean field (nMF) and Thouless-Anderson-Palmer (TAP) approximations are methods used for this reconstruction.

Purpose of the Study:

  • To compare the effectiveness of nMF and TAP approximations in reconstructing network structures from dynamical data.
  • To investigate the performance of TAP approximation using two distinct methods: iterative and direct cubic equation solving.

Main Methods:

  • Network inference using naive mean field (nMF) approximation.
  • Network inference using Thouless-Anderson-Palmer (TAP) approximation with iterative and direct cubic equation solving methods.
  • Analysis of the asymmetric Sherrington-Kirkpatrick (aS-K) model under asynchronous update.
  • Investigation of the influence of temperature and data length on reconstruction accuracy.

Main Results:

  • A critical temperature T(c)≈2.1 was identified for the asymmetric Sherrington-Kirkpatrick model.
  • Both TAP methods yielded consistent results when the iterative method converged.
  • TAP approximation demonstrated superior performance compared to nMF, particularly at lower temperatures and with increased data length.
  • The performance gap between TAP and nMF diminished as temperature increased.

Conclusions:

  • Thouless-Anderson-Palmer approximation offers improved network reconstruction accuracy over naive mean field, especially under low-temperature conditions.
  • The direct solution of cubic equations provides a reliable alternative to iterative methods for TAP approximation.
  • Network reconstruction accuracy improves with longer data lengths for both methods, with TAP showing greater benefits.