Alignment-free Methods for Classification of Metagenomic Data
| but.event.date | 28.04.2016 | cs |
| but.event.title | Student EEICT 2016 | cs |
| dc.contributor.author | Vaněčková, Tereza | |
| dc.date.accessioned | 2018-07-10T12:48:15Z | |
| dc.date.available | 2018-07-10T12:48:15Z | |
| dc.date.issued | 2016 | cs |
| dc.description.abstract | Metagenomics studies microbial communities by analyzing their genomic content directly sequenced from the environment. In this contribution, alignment-free methods based on word frequency will be introduced. It has been proven, that these methods are effective in processing of short metagenomic sequence reads produced by Next-Generation Sequencing technologies. To evaluate the potential of word frequency based methods, the k-mer analysis was applied on simulated dataset of metagenomic sequence reads with length of 600 nucleotides. Then the data were enrolled for a hierarchical cluster analysis. Results have shown that the proposed method is able to cluster genome fragments of the same taxa. | en |
| dc.format | text | cs |
| dc.format.extent | 244-246 | cs |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Proceedings of the 22nd Conference STUDENT EEICT 2016. s. 244-246. ISBN 978-80-214-5350-0 | cs |
| dc.identifier.isbn | 978-80-214-5350-0 | |
| dc.identifier.uri | http://hdl.handle.net/11012/83930 | |
| dc.language.iso | en | cs |
| dc.publisher | Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
| dc.relation.ispartof | Proceedings of the 22nd Conference STUDENT EEICT 2016 | en |
| dc.relation.uri | http://www.feec.vutbr.cz/EEICT/ | cs |
| dc.rights | © Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
| dc.rights.access | openAccess | en |
| dc.subject | metagenomics | en |
| dc.subject | alignment-free | en |
| dc.subject | nucleotide word frequency | en |
| dc.subject | hierarchical clustering | en |
| dc.title | Alignment-free Methods for Classification of Metagenomic Data | en |
| dc.type.driver | conferenceObject | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
| eprints.affiliatedInstitution.department | Fakulta elektrotechniky a komunikačních technologií | cs |
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