Application Of Optimization Algorithms To The Genome Assembly
Alternative metrics PlumXhttp://hdl.handle.net/11012/138303
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The paper results from development of new sequencing methods together with the need of suitable genome assembly algorithms. It combines the genomic signal processing, correlation techniques and optimization algorithms for solving assembly task. Genomic signals are made by conversion of letter-based DNA into the form of digital signal, thus the methods of digital signal processing can be applied. Possible overlaps between reads converted into signals are found by computing correlation coefficient similarly to cross-correlation. We acquire similarity matrix and the task is to find the path through it achieving minimum distance criterion. For the task, the two optimization techniques were employed: ant colony optimization (ACO) and simulated annealing (SA). The result implies the possibility of using the ACO at the task of creating path through similarly to graphtheory-based algorithms.
Document typePeer reviewed
Document versionxmlui.vut.verze.Publishers's version
SourceProceedings of the 24th Conference STUDENT EEICT 2018. s. 595-599. ISBN 978-80-214-5614-3
- Student EEICT 2018