algorithm to compare the similarity of a protein sequence and a protein profile and compute an optimal alignment More...

#include <pp_simscore.hh>

Public Member Functions
	SimilarityScore (double g, double b, double g_i, double iw1, double iw2, double e_i, double e_n)

void	printInterBlock ()

bool	SimilarityMatrix_empty ()

void	printAlignmentDB ()

void	printBlockPos ()

pair< double, double >	avgArgMaxProb ()

void	readFiles (const char seqFileName, const char profileFileName)

void	fillSimilarityMatrix ()

void	backtrackingDB (int number_Alignments)

double	score ()

void	printSimilarityMatrix ()

void	printAlignment ()

Public Attributes
std::vector< std::vector< AlignmentElement > >	alignments

std::vector< pair< std::string, PrflAlignment > >	alignmentsReadable

Detailed Description

algorithm to compare the similarity of a protein sequence and a protein profile and compute an optimal alignment

Based on the Needleman-Wunsch algorithm, it computes with a SimilarityMatrix the optimal global alignment score. For every column of the protein profile and every position in the protein sequence the optimal alignment score up to that position will be computed. Here, the columns of the SimilarityMatrix are the proteins of the protein sequence and the rows of the SimilarityMatrix are the columns of the protein profile. At the moment, gaps in the alignment are allowed.

Parameters

g gap cost in inter-block region, b: gap cost for an intra-block gap, g_i: gap cost for a gap in the alignment of intron positions, iw1: intron weight for the intron score in an intra-block region, iw2: intron weight for the intron score in an intra-block region, e_i: pseudocount parameter for epsilon1, e_n pseudocount parameter for epsilon2

Author: Lars Gabriel

The documentation for this class was generated from the following files:

include/pp_simscore.hh
src/pp_simscore.cc

Public Member Functions

Public Attributes

Detailed Description