Show simple item record

dc.contributor.authorHamzeiy, Hamid
dc.contributor.authorYousef, Malik
dc.contributor.authorAllmer, Jens
dc.date.accessioned2018-02-20T07:37:15Z
dc.date.available2018-02-20T07:37:15Z
dc.date.issued2014
dc.identifier.citationHamzeiy, H., Yousef, M., and Allmer, J. (2014). Computational methods for microRNA target prediction. Methods in Molecular Biology, 1107, 207-221. doi:10.1007/978-1-62703-748-8_12en_US
dc.identifier.issn1064-3745
dc.identifier.urihttp://hdl.handle.net/11147/6807
dc.description.abstractMicroRNAs (miRNAs) are important players in gene regulation. The final and maybe the most important step in their regulatory pathway is the targeting. Targeting is the binding of the miRNA to the mature RNA via the RNA-induced silencing complex. Expression patterns of miRNAs are highly specific in respect to external stimuli, developmental stage, or tissue. This is used to diagnose diseases such as cancer in which the expression levels of miRNAs are known to change considerably. Newly identified miRNAs are increasing in number with every new release of miRBase which is the main online database providing miRNA sequences and annotation. Many of these newly identified miRNAs do not yet have identified targets. This is especially the case in animals where the miRNA does not bind to its target as perfectly as it does in plants. Valid targets need to be identified for miRNAs in order to properly understand their role in cellular pathways. Experimental methods for target validations are difficult, expensive, and time consuming. Having considered all these facts it is of crucial importance to have accurate computational miRNA target predictions. There are many proposed methods and algorithms available for predicting targets for miRNAs, but only a few have been developed to become available as independent tools and software. There are also databases which collect and store information regarding predicted miRNA targets. Current approaches to miRNA target prediction produce a huge amount of false positive and an unknown amount of false negative results, and thus the need for better approaches is evermore evident. This chapter aims to give some detail about the current tools and approaches used for miRNA target prediction, provides some grounds for their comparison, and outlines a possible future.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.isversionof10.1007/978-1-62703-748-8_12en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBioinformaticsen_US
dc.subjectComputational biologyen_US
dc.subjectMicroRNAsen_US
dc.subjectTarget predictionen_US
dc.titleComputational methods for microRNA target predictionen_US
dc.typearticleen_US
dc.contributor.authorIDTR107974en_US
dc.contributor.institutionauthorHamzeiy, Hamid
dc.contributor.institutionauthorAllmer, Jens
dc.relation.journalMethods in Molecular Biologyen_US
dc.contributor.departmentİYTE, Fen Fakültesi, Moleküler Biyoloji ve Genetik Bölümüen_US
dc.identifier.volume1107en_US
dc.identifier.startpage207en_US
dc.identifier.endpage221en_US
dc.identifier.scopusSCOPUS:2-s2.0-84934441309
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record