Pregled bibliografske jedinice broj: 773703
De novo metagenomic assembly using Bayesian model-based clustering
De novo metagenomic assembly using Bayesian model-based clustering, 2014., diplomski rad, diplomski, Fakultet elektrotehnike i računarstva, Zagreb
CROSBI ID: 773703 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
De novo metagenomic assembly using Bayesian model-based clustering
Autori
Dvorničić, Mirta
Vrsta, podvrsta i kategorija rada
Ocjenski radovi, diplomski rad, diplomski
Fakultet
Fakultet elektrotehnike i računarstva
Mjesto
Zagreb
Datum
01.07
Godina
2014
Stranica
46
Mentor
Šikić, Mile
Ključne riječi
metagenomics; de novo assembly; hierarchical clustering; Bayesian information criterion
Sažetak
Microbial communities influence almost every aspect of our lives. Metagenomics aims to expand our knowledge of those communities by analyzing DNA samples extracted directly from their environments. Metagenomic studies still rely mostly on manual interventions and single genome assembly tools which are unaware of the nature of metagenomic data. In this thesis, a Bayesian model-based hierarchical clustering approach to aid in metagenomic assembly called Sigma is presented. Sigma is combined with an optimal single genome scaffolder Opera to show that metagenomic assembly problem can be accurately and automatically reduced to single genome assembly problem by systematically exploiting assembly information. Comparisons on simulated and real datasets show that this pipeline (OperaMS) outperforms state-ofthe- art single genome (Velvet, SOAPdenovo) and metagenomic (MetaVelvet, Bambus2) assembly tools.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Mile Šikić
(mentor)