Accurate statistics for local sequence alignment with position-dependent scoring by rare-event sampling

Sequence Alignment by Rare Event Simulation

We present a new stochastic method for finding the optimal alignment of DNA sequences. The method works by generating random paths through a graph (the edit graph) according to a Markov chain. Each path is assigned a score, and these scores are used to modify the transition probabilities of the Markov chain. This procedure converges to a fixed path through the graph, corresponding to the optima...

Sampling rare events: statistics of local sequence alignments.

A method to calculate probability distributions in regions where the events are very unlikely (e.g., p approximately 10(-40)) is presented. The basic idea is to map the underlying model on a physical system. The system is simulated at a low temperature, such that preferably configurations with originally low probabilities are generated. Since the distribution of such a physical system is known,...

Protein Sequence Alignment Analysis by Local Covariation: Coevolution Statistics Detect Benchmark Alignment Errors

The use of sequence alignments to understand protein families is ubiquitous in molecular biology. High quality alignments are difficult to build and protein alignment remains one of the largest open problems in computational biology. Misalignments can lead to inferential errors about protein structure, folding, function, phylogeny, and residue importance. Identifying alignment errors is difficu...

Local alignment statistics.

Nonequilibrium Rare-Event Sampling

This paper by Berryman and Schilling [1] has been in the literature for a year now, and is a valuable addition to the battery of techniques available to study nonequilibrium processes by molecular simulation; but it seems not to have attracted much attention. In the challenging field of " rare events " , there are three broad target areas, of increasing degree of difficulty: (a) systems in equi...