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Jelović, Ana (Beograd , 2022)[more][less]
Zusammenfassung: n the first part of this dissertation different repeat types are defined as well as repeats that satisfy motif masks. A method for precise repeat finding in input sequences of arbitrary length has been described. As the input sequences can be very long, the number of found repeats can also be large. For that reason it is important that the method also includes filtering found repeats based on the expected number of their occurrences. The method was first applied to protein sequences in which experimentally confirmed T-cell epitopes from the IEDB database were registered. Association rules were applied to the found repeats in order to construct a model that would enable the prediction of the positions of T-cell epitopes in protein sequences. In this way, it would indicate to researchers a region in the protein sequence where an epitope can be expected with high confidence. In the case of T-cell epitopes, a large number of rules with high confidence was found. These rules can be considered as reliable predictors of the position of T-cell epitopes within the protein sequences. Based on the results found, association rules were formed that characterize the epitopes and the repeats associated with them in more detail. As a large number of results were found, only their part is presented in this disser- tation. On the basis of the strings that determine the repeat, a motif mask that the repeat needs to satisfy was searched for. The entire procedure was applied to both direct non-complementary repeats and indirect non-complementary repeats. With similar results, the entire procedure was applied to B-cell epitopes on data from the IEDB database. Data on experimentally confirmed short linear motifs were taken from the ELM database. In protein sequences where short linear motifs were registered, repeats were searched for and association rules were applied to them. The rules with high confidence have been singled out in particular. On the basis of the results found, motif masks that repeats with high confidence would satisfy were searched for. URI: http://hdl.handle.net/123456789/5442 Dateien zu dieser Ressource: 1
Ana_Jelovic_tekst_doktorata.pdf ( 6.127Mb ) -
Mitrašinović, Ana (Beograd , 2022)[more][less]
Zusammenfassung: The subject of this dissertation is to study the effects of galaxy flybys on the structural evolution of galaxies. Galaxy flybys are very close interactions that do not result in a merger. With the high frequency in the late Universe, their role in the evolution of galaxies is significant. Earlier studies focused on equal-mass flybys, which are extremely rare. We focus on typical flybys with a lower mass ratio. We aim to explore the structure and evolution of galaxies in greater detail and demonstrate that these flybys are just as important as equal-mass ones. We performed a series of N body simulations of typical flybys with varying impact para- meters. We demonstrated the applicability and importance of isolated N body simulations and developed an efficient method for reliable bar detection in galaxy discs. For the first time, we examined the evolution of the secondary galaxy, focusing on its dark matter mass loss. The results show that the leftover mass follows logarithmic growth law with impact parameter and suggest that flybys contribute to the formation of dark matter-deficient galaxies. The primary galaxy is affected in a similar way as in equal-mass flybys. Bars form in closer flybys, two-armed spirals form during all flybys, and the dark matter halo spins up. Most of the parameters of these structures are correlated or anti-correlated with the impact parameter. We also noticed that a double bar could form as evolving spirals wrap around the early-formed bar. We successfully demonstrated that frequent, typical flybys with lower mass ratios signifi- cantly affect the evolution of galaxies, producing various observed effects. Our results should serve as a warning not to disregard these interactions in future studies. URI: http://hdl.handle.net/123456789/5441 Dateien zu dieser Ressource: 1
mitrasinovic_ana.pdf ( 5.370Mb ) -
Jovanović, Jasmina (Beograd , 2022)[more][less]
Zusammenfassung: The analysis of biological sequence similarity between different species is significant in identifying functional, structural or evolutionary relationships among the species. Biological sequence similarity and analysis of newly discovered nucleotide and amino acid sequences are demanding tasks in bioinformatics. As biological data is growing exponentially, new and innovative algorithms are needed to be constantly developed to get faster and more effective data processing. The challenge in sequence similarity analysis algorithms is that sequence does not always have obvious features and the dimension of sequence features may be very high for applying regular feature selection methods on sequences. It is important to have a simple and effective algorithm for determining biological sequence relationships. This thesis proposes two new methods for sequence transformation in feature vectors that takes into consideration statistically significant repetitive parts of analyzed sequences, as well as includes different approaches for determination of nucleotide sequence similarity and sequence classification for predicting taxonomy groups of biological sequence data. The first method is based on information theory and fact that both position and frequency of repeated sequences are not expected to occur with the identical presence in a random sequence of the same length. The second method includes building signatures of biological sequences and profiles of taxonomic classes based on repetitive parts of sequences and distances between these repeats. Proposed methods have been validated on multiple data sets and compared with results obtained using different well known and accepted methods in this field like BLAST, Clustal Omega and methods based on k-mers. Resulted precision for proposed methods is close to values provided for existing methods for the majority of tested data-sets, and time performance depends strictly to used infrastructure and sequence type. Methods provide results that are comparable with other commonly used methods focused on resolving the same problem, taking into consideration statistically significant repetitive parts of sequences with different characteristics. URI: http://hdl.handle.net/123456789/5440 Dateien zu dieser Ressource: 1
JasminaJovanovic.pdf ( 3.984Mb ) -
Protić, Jana (Beograd , 2021)[more][less]
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Savić, Marija (Beograd , 2022)[more][less]
URI: http://hdl.handle.net/123456789/5438 Dateien zu dieser Ressource: 1
SevićMarija.pdf ( 1.787Mb )