WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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2011 - 20132

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  • Conference Object
    Citation - WoS: 6
    Citation - Scopus: 8
    Comparison of Four Ab Initio Microrna Prediction Tools
    (SciTePress, 2013) Saçar, Müşerref Duygu; Allmer, Jens
    MicroRNAs are small RNA sequences of 18-24 nucleotides in length, which serve as templates to drive post transcriptional gene silencing. The canonical microRNA pathway starts with transcription from DNA and is followed by processing by the Microprocessor complex, yielding a hairpin structure. This is then exported into the cytosol where it is processed by Dicer and next incorporated into the RNA induced silencing complex. All of these biogenesis steps add to the overall specificity of miRNA production and effect. Unfortunately, experimental detection of miRNAs is cumbersome and therefore computational tools are necessary. Homology-based miRNA prediction tools are limited by fast miRNA evolution and by the fact that they are template driven. Ab initio miRNA prediction methods have been proposed but they have not been analyzed competitively so that their relative performance is largely unknown. Here we implement the features proposed in four miRNA ab initio studies and evaluate them on two data sets. Using the features described in Bentwich 2008 leads to the highest accuracy but still does not provide enough confidence into the results to warrant experimental validation of all predictions in a larger genome like the human genome. Copyright © 2013 SCITEPRESS - Science and Technology Publications.
  • Conference Object
    Citation - WoS: 4
    Citation - Scopus: 4
    Mining Frequent Patterns From Microarray Data
    (Institute of Electrical and Electronics Engineers Inc., 2011) Yıldız, Barış; Şelale, Hatice
    The rapid development of computers and increasing amount of collected data made data mining a popular analysis tool. Data mining research is interrelated to many fields and one of the most important ones is bioinformatics. Among many techniques, mining association rules or frequent patterns is one of the most studied techniques in computer science and it is applicable to bioinformatics. Association analysis of gene expressions may be used as decision support mechanism for finding genes that are in same pathway. In this work, publicly available yeast microarray data has been analyzed using an efficient frequent pattern mining algorithm Matrix Apriori and frequently co-over-expressed genes have been identified. © 2011 IEEE.