November 14, 2012

Poravnanja više slijedova je jedan od temeljnih problema bioinformatike. Za analitično poravnanje dva slijeda već se desecima godina koristi Smith-Waterman obitelj algoritama, no zbog svoje velike prostorne i vremenske složenosti ti algoritmi nisu pogodni za poravnanje većeg broja slijedova. Kao prvi korak poravnanja većeg broja slijedova izgrađuje se graf poravnanja parcijalnog uređaja koristeći modificirani Smith-Waterman algoritam. Tako izgrađen graf pogodan je za daljnu analizu slijedova: generiranje poravnanja većeg broja slijedova te pronalaženja konsenzusa. U ovom radu predstavljen je algoritam za spajanje dva već postojeća grafa poravnanja parcijalnog uređenja koji zbog korištenja već izgrađenog grafa smanjuje broj koraka potrebnih za igradnju većeg grafa.Sequence alignment is one of fundemental problems in bionformatics. Alignment of two sequences is done using Smith-Waterman family of algorithms. These algorithms are not useable for alignment of multiple sequences because of theirs big time and memory complexity. Partial order alignment (POA) graph is a first step of calculating multiple sequence alignment efficiently. POA graph is suitable for further analysis of sequences: calculation of multiple sequence alignment and concensus generation. In this thesis algorithm for merging two already existing POA graph is presented. Algorithm reduces number of steps needed to build bigger POA graphs by reusing parts of existing ones

Alvira : comparative genomics of viral strains

The Alvira tool is a general purpose multiple sequence alignment viewer with a special emphasis on the comparative analysis of viral genomes. This new tool has been devised specifically to address the problem of the simultaneous analysis of a large number of viral strains. The multiple alignment is embedded in a graph that can be explored at different levels of resolution

Back-translation for discovering distant protein homologies

Frameshift mutations in protein-coding DNA sequences produce a drastic change in the resulting protein sequence, which prevents classic protein alignment methods from revealing the proteins' common origin. Moreover, when a large number of substitutions are additionally involved in the divergence, the homology detection becomes difficult even at the DNA level. To cope with this situation, we propose a novel method to infer distant homology relations of two proteins, that accounts for frameshift and point mutations that may have affected the coding sequences. We design a dynamic programming alignment algorithm over memory-efficient graph representations of the complete set of putative DNA sequences of each protein, with the goal of determining the two putative DNA sequences which have the best scoring alignment under a powerful scoring system designed to reflect the most probable evolutionary process. This allows us to uncover evolutionary information that is not captured by traditional alignment methods, which is confirmed by biologically significant examples.Comment: The 9th International Workshop in Algorithms in Bioinformatics (WABI), Philadelphia : \'Etats-Unis d'Am\'erique (2009