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Related Experiment Videos

Sampling rare events: statistics of local sequence alignments.

Alexander K Hartmann1

  • 1Department of Physics, University of California, Santa Cruz, California 95064, USA. hartmann@bach.ucsc.edu

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|June 13, 2002
PubMed
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This study introduces a novel simulation method to accurately calculate extremely low probability distributions. The technique maps models to physical systems, enabling efficient generation of rare events for applications like protein sequence alignment.

Area of Science:

  • Computational biology
  • Statistical mechanics
  • Bioinformatics

Background:

  • Calculating probabilities for rare events (p ~ 10^-40) is computationally challenging.
  • Traditional methods struggle with extreme probability distributions.

Purpose of the Study:

  • To present a new method for calculating probability distributions in rare event regions.
  • To apply this method to analyze protein sequence alignment scores.

Main Methods:

  • Mapping the probability model onto a physical system.
  • Simulating the physical system at low temperatures to favor low-probability configurations.
  • Using the known distribution of the physical system to derive the original unbiased distribution.

Main Results:

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  • The method successfully calculates probabilities in regions of extreme rarity.
  • The local alignment of protein sequences was studied as an application.
  • The deviation of optimal alignment scores' distribution from extreme-value distribution was quantified and found to decrease with increasing sequence length.

Conclusions:

  • The proposed simulation method is effective for rare event probability calculations.
  • The findings provide insights into the statistical properties of protein sequence alignment scores.