Classification of unknown organisms in a simulated metagenomic sample

Velikom primjenom bioinformatike i metagenomike, ovo istraživanje se fokusiralo na klasifikaciju nepoznatih organizama u simuliranim metagenomskim podatcima. Korištenjem naprednih alata i algoritama, analizirane su genetske sekvence kako bi identificirali i klasificirali različite bakterijske taksonomske jedinice. Uz pomoć tri ključne baze podataka, kombiniranjem podataka o sekvencama s referentnim informacijama, uspješno smo pružili uvid u složene mikrobne zajednice prisutne u metagenomima.Using bioinformatics and metagenomics to a wide extent, this research focuses on the classification of unknown microorganisms in a set of simulated metagenomic data. Genetic sequences were analysed with advanced tools and algorithms in order to identify and classify different bacterial taxonomic units. Such tools have ultimately combined acquired data related to the genomic sequences with the appropriate references by using three key data bases in order to provide further insight into complex microbial communities that are present in metagenomic samples