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Related Experiment Videos

Global network alignment using multiscale spectral signatures.

Rob Patro1, Carl Kingsford

  • 1Center for Bioinformatics and Computational Biology, Institute for Advanced Computer Studies and Department of Computer Science, University of Maryland, College Park, MD 20742, USA. rob@cs.umd.edu

Bioinformatics (Oxford, England)
|October 11, 2012
PubMed
Summary
This summary is machine-generated.

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Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single stretching vibration...

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GHOST, a novel network aligner, accurately maps proteins between species using spectral signatures. This tool identifies larger, biologically significant shared subnetworks, advancing comparative network biology.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Protein interaction networks offer a systems-level view of biological processes.
  • Global network alignment is crucial for comparing protein networks across species, aiding in functional inference and evolutionary studies.

Purpose of the Study:

  • To introduce GHOST, a novel global pairwise network aligner.
  • To improve the accuracy and biological relevance of network alignments.

Main Methods:

  • GHOST utilizes a unique spectral signature to quantify topological similarity between subnetworks.
  • The aligner incorporates a seed-and-extend global alignment phase coupled with a local search refinement.

Main Results:

Related Experiment Videos

  • GHOST demonstrates superior performance on various network alignment benchmarks.
  • The spectral signature is highly discriminative, and alignments are robust to noise.
  • GHOST recovers larger and more biologically significant shared subnetworks compared to existing methods.

    • Conclusions:

    • GHOST represents a significant advancement in global network alignment.
    • Its ability to identify robust and biologically meaningful alignments facilitates cross-species comparative analysis.