Circular RNA–MicroRNA–MRNA interaction predictions in SARS-CoV-2 infection

Autor: Yılmaz Mehmet Demirci, Müşerref Duygu Saçar Demirci
Přispěvatelé: AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Biyomühendislik Bölümü, Demirci, Yilmaz Mehmet, Demirci, Muserref Duygu Sacar
Rok vydání: 2021
Předmět:
Zdroj: Journal of Integrative Bioinformatics
Journal of Integrative Bioinformatics, Vol 18, Iss 1, Pp 45-50 (2021)
ISSN: 1613-4516
DOI: 10.1515/jib-2020-0047
Popis: This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK, Grant No: 120E042). Different types of noncoding RNAs like microRNAs (miRNAs) and circular RNAs (circRNAs) have been shown to take part in various cellular processes including post-transcriptional gene regulation during infection. MiRNAs are expressed by more than 200 organisms ranging from viruses to higher eukaryotes. Since miRNAs seem to be involved in host-pathogen interactions, many studies attempted to identify whether human miRNAs could target severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNAs as an antiviral defence mechanism. In this work, a machine learning based miRNA analysis work flow was developed to predict differential expression patterns of human miRNAs during SARS-CoV-2 infection. In order to obtain the graphical representation of miRNA hairpins, 36 features were defined based on the secondary structures. Moreover, potential targeting interactions between human circRNAs and miRNAs as well as human miRNAs and viral mRNAs were investigated. Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) 120E042
Databáze: OpenAIRE