20.500.12556/RUL-114119 Pregled in primerjava računskih pristopov za analizo ritmičnega izražanja genov Overview and comparison of computational approaches for the analysis of rhythmicity in gene expression data Pri modeliranju bioloških procesov pogosto naletimo na vzorce, ki se težko opišejo z obstoječimi metodami modeliranja in napovedovanja. To še posebno velja za analizo ritmičnega izražanja, saj se mora metoda spopasti z variacijami amplitud, period, faznih zamikov ter manjšim vzorcem, ki je pogosto onesnažen s človeškimi napakami. Zato je pomembno vedeti, kako se obnesejo obstoječe metode za take primere, in katere med njimi so bolj primerne in katere manj. Delo se posveča pregledu nekaterih obstoječih metod in optimalnemu izboru implementacij med obravnavanimi glede na doseženo točnost, ki jo dosežejo v petih serijah sintetično generiranih podatkov z različnimi parametri. S pomočjo rezultatov določimo, katere metode se obnesejo v katerih pogojih in kateri pogoji vzorčenja proizvedejo najbolj primerne podatke za analize. Na koncu izvedbo analize ritmičnosti naredimo še na primeru transkriptomskih podatkov, ki so bili pridobljeni iz javno dostopne podatkovne baze GEO. When modelling biological processes, we often find ourselves faced with complex patterns, that cannot be adequately described by existing methods of modelling and data prediction. That applies well when data contains rhythmical elements, as chosen method must be able to process amplitude, period and acrophase variations coupled with smaller data set, which is often biased by human error. With this in mind, it is important to know which methods currently in use can be best suited for such problems. In this work we will focus on few selected methods and their performance in five different synthetically generated data series. With the help of obtained results we will be able to determine which method is better suited for which conditions and performs best in most series, as well as which sampling conditions produce most and least suited data for further computational analyses. We demonstrate the application of selected methods on the analysis of transcriptomic data obtained from GEO database. modeliranje računska biologija sistemska biologija regresija cirkadiani ritmi modelling computational biology systemic biology regression circadian rhythms true false false Slovenski jezik Angleški jezik Diplomsko delo/naloga 2020-02-18 10:20:11 2020-02-18 10:20:19 2024-01-03 07:40:30 0000-00-00 00:00:00 2020 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 23362 1538535619 Miskic_David_-_Pregled_in_primerjava_racunskih_pristopov_za_analizo_ritmicnega_izrazanja_genov.pdf Miskic_David_-_Pregled_in_primerjava_racunskih_pristopov_za_analizo_ritmicnega_izrazanja_genov.pdf 1 B24EC7033E286567131C202B041B1B7C 3c357425aa8d47208db97e8370e5478844162b1f50fbd184b22bd3d41f483da0 2f839411-a1b8-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=126259 Fakulteta za računalništvo in informatiko 0 0 0