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MISTIC: Mutual information server to infer coevolution.

Franco L Simonetti1, Elin Teppa, Ariel Chernomoretz

  • 1Bioinformatics Unit, Fundación Instituto Leloir, Av. Patricias Argentinas 435, C1405BWE, Buenos Aires, Argentina.

Nucleic Acids Research
|May 30, 2013
PubMed
Summary
This summary is machine-generated.

MISTIC is a novel web server that visualizes protein family information from multiple sequence alignments (MSA). It offers a unique, integrated view of coevolutionary networks using mutual information (MI) for enhanced analysis.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Analyzing protein families requires understanding coevolutionary relationships within multiple sequence alignments (MSA).
  • Existing tools often lack integrated visualization of complex information like mutual information (MI) networks.

Purpose of the Study:

  • To introduce MISTIC, a web server for graphical representation and analysis of information within MSAs.
  • To provide an integrated and visually rich view of protein family coevolutionary networks.

Main Methods:

  • Development of a web server (MISTIC) for processing MSAs.
  • Utilizing circos representation for visualizing MI networks, sequence conservation, and residue scores.
  • Implementing interactive tools for network exploration and node attribute customization (e.g., conservation, secondary structure).

Main Results:

  • MISTIC generates a comprehensive graphical output integrating mutual information (MI) between residue pairs, sequence conservation, and cumulative/proximity MI scores.
  • The server provides an interactive interface for exploring and characterizing MI networks.
  • Novel visualization of cumulative and proximity MI concepts using circos representation.

Conclusions:

  • MISTIC offers a unique and comprehensive approach to visualizing and analyzing information within MSAs.
  • The tool facilitates a deeper understanding of protein family coevolutionary dynamics.
  • The circos representation and novel MI concepts provide valuable insights not available in other web servers.