engleski

Combinatorial optimization algorithms for (pseudo)alignment in bioinformatics

The field of bioinformatics is a fast growing interdisciplinary field with a strong contribution from mathematics and computer science. This thesis will deal with mathematical problems and algorithmic challenges from that field. Its first focus will be the comparison of hierarchic structures, mainly phylogenetic trees, which is used to explain various biological processes such as the evolution of the species. We will study mathematical models and algorithmic techniques which quantify the distance between such structures as means of determining the similarities or dissimilarities between them. The focus will be given to formulating the problem based on matching in the context of integer linear programming. Our goal will be to find a novel solution which respects the ancestry relations defined by those hierarchical structures and is often overlooked in the current research. Our main result will be given in a form of a software tool - Trajan, which will be tested on both the real world and simulated data. The second focus of the thesis will come from the problem of sequencing the RNA molecule. It is a combinatorial process of reconstruction of the RNA molecule from short nucleotide sequences which is used to analyze the transcriptome of a biological sample. Many recent studies consider a problem of quantification and classification of unannotated splicing events which often occur due to the mutations caused by abnormal state of the organism, e.g. cancer. We will present another software tool, called fortuna, which brings together high accuracy and fast running times to the analysis of the alternative splicing events unlike any of the well established competitor tools.

phylogenetic trees ; Trajan ; distance ; integer linear programming ; branch-and-cut method ; clique constraints ; RNA-Seq ; fortuna ; alternative splicing ; alignment ; quantification

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