PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397
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Article Citation - WoS: 2Citation - Scopus: 1Computational Prediction of MicroRNAs in Histoplasma Capsulatum(Academic Press Ltd- Elsevier Science Ltd, 2020-11) Demirci, Mueserref Duygu Sagar; Saçar Demirci, Müşerref DuyguMicroRNAs (miRNAs) are small and non-coding RNAs that regulate gene expression through post-transcriptional regulation. Although, the standard miRNA repository, MiRBase, lists more than 200 organisms having miRNA mediated regulation mechanism and thousands of miRNAs, there is not enough information about miRNAs of fungal species. Considering that there are various fungal pathogens causing disease phenotypes, it is important to search for miRNAs of those organisms. The leading cause of endemic mycosis in the USA is a fungal disease known as histoplasmosis, which is resulted by infection with a fungal intracellular parasite, Histoplasma capsulatum (H. capsulatum). In this work, genomes of H. capsulatum strains NAm1 and G217B were explored for potential miRNA like sequences and structures. Through a complex workflow involving miRNA detection and target prediction, several miRNA candidates of H. capsulatum and their possible targets in human were identified. The results presented here indicate that H. capsulatum might be one of the fungal pathogens having a miRNA based post-transcriptional gene regulation mechanism and it might have a miRNA mediated host - parasite interaction with human.Book Part Citation - WoS: 20Citation - Scopus: 27Computational Prediction of Functional MicroRNA-mRNA Interactions(Humana Press Inc, 2019) Demirci, Muserref Duygu Sacar; Yousef, Malik; Allmer, Jens; Saçar Demirci, Müşerref DuyguProteins have a strong influence on the phenotype and their aberrant expression leads to diseases. MicroRNAs (miRNAs) are short RNA sequences which posttranscriptionally regulate protein expression. This regulation is driven by miRNAs acting as recognition sequences for their target mRNAs within a larger regulatory machinery. A miRNA can have many target mRNAs and an mRNA can be targeted by many miRNAs which makes it difficult to experimentally discover all miRNA-mRNA interactions. Therefore, computational methods have been developed for miRNA detection and miRNA target prediction. An abundance of available computational tools makes selection difficult. Additionally, interactions are not currently the focus of investigation although they more accurately define the regulation than pre-miRNA detection or target prediction could perform alone. We define an interaction including the miRNA source and the mRNA target. We present computational methods allowing the investigation of these interactions as well as how they can be used to extend regulatory pathways. Finally, we present a list of points that should be taken into account when investigating miRNA-mRNA interactions. In the future, this may lead to better understanding of functional interactions which may pave the way for disease marker discovery and design of miRNA-based drugs.Book Part Citation - Scopus: 4Computational Detection of Pre-MicroRNAs(Humana Press Inc., 2021-08-26) Saçar Demirci, Müşerref DuyguMicroRNA (miRNA) studies have been one of the most popular research areas in recent years. Although thousands of miRNAs have been detected in several species, the majority remains unidentified. Thus, finding novel miRNAs is a vital element for investigating miRNA mediated posttranscriptional gene regulation machineries. Furthermore, experimental methods have challenging inadequacies in their capability to detect rare miRNAs, and are also limited to the state of the organism under examination (e.g., tissue type, developmental stage, stress-disease conditions). These issues have initiated the creation of high-level computational methodologies endeavoring to distinguish potential miRNAs in silico. On the other hand, most of these tools suffer from high numbers of false positives and/or false negatives and as a result they do not provide enough confidence for validating all their predictions experimentally. In this chapter, computational difficulties in detection of pre-miRNAs are discussed and a machine learning based approach that has been designed to address these issues is reviewed. © 2021 Elsevier B.V., All rights reserved.