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dc.contributor.supervisorDomaratzki, Michael (Computer Science)en_US
dc.contributor.authorMahdi, Md Safiur Rahman
dc.date.accessioned2015-08-25T23:54:53Z
dc.date.available2015-08-25T23:54:53Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/1993/30677
dc.description.abstractMicroRNAs (miRNAs) play a vital role in regulating gene expression. Detecting conserved and novel miRNAs in very large genomic datasets generated using next generation sequencing platforms is a new research area in the field of gene regulation, but finding useful miRNA information from a large wheat genome is a challenging research project. We propose to design a toolchain that will identify conserved miRNAs using various software tools such as Basic Local Alignment Search Tool (BLAST), Bowtie 2, MAFFT and RNAfold. Our toolchain identified 36 wheat conserved miRNA families that matched with 232 experimental sequences. Moreover, we found 87 plant conserved miRNA families that matched between 613 experimental sequences and the miRBase dataset. In addition, we observed significant differential expression for the wheat exposed to the heat stress compared to those exposed to light and UV stresses or no stress (control).en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBioinformaticsen_US
dc.subjectDifferential gene expressionen_US
dc.subjectWheaten_US
dc.subjectMicro RNAsen_US
dc.titleIdentifying conserved microRNAs in a large dataset of wheat small RNAsen_US
dc.typeinfo:eu-repo/semantics/masterThesis
dc.typemaster thesisen_US
dc.degree.disciplineComputer Scienceen_US
dc.contributor.examiningcommitteeHemmati, Hadi (Computer Science) Cloutier, Sylvie (Plant Science)en_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.noteOctober 2015en_US


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