Computationally predicted SARS-COV-2 encoded microRNAs target NFKB, JAK/STAT and TGFB signaling pathways
Yazarlar (5)
Merve Nur Aydemir İstanbul Üniversitesi, Türkiye
Arş. Gör. Habeş Bilal AYDEMİR Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Ergün Pınarbaşı Sivas Cumhuriyet Üniversitesi, Türkiye
Ertan Mahir Korkmaz Sivas Cumhuriyet Üniversitesi, Türkiye
Mahir Budak Sivas Cumhuriyet Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(ESCI dergilerinde yayınlanan tam makale)
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| Dergi Adı | Gene Reports | ||
| Dergi ISSN | 2452-0144 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | ESCI | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2021 |
| Kabul Tarihi | 12-04-2026 | Yayınlanma Tarihi | – |
| Cilt / Sayı / Sayfa | 22 / 101012 / 101012–0 | DOI | 10.1016/j.genrep.2020.101012 |
| Makale Linki | https://dx.doi.org/10.1016/j.genrep.2020.101012 | ||
| Özet |
| Recently an outbreak that emerged in Wuhan, China in December 2019, spread to the whole world in a short time and killed >1,410,000 people. It was determined that a new type of beta coronavirus called severe acute respiratory disease coronavirus type 2 (SARS-CoV-2) was causative agent of this outbreak and the disease caused by the virus was named as coronavirus disease 19 (COVID19). Despite the information obtained from the viral genome structure, many aspects of the virus-host interactions during infection is still unknown. In this study we aimed to identify SARS-CoV-2 encoded microRNAs and their cellular targets. We applied a computational method to predict miRNAs encoded by SARS-CoV-2 along with their putative targets in humans. Targets of predicted miRNAs were clustered into groups based on their biological processes, molecular function, and cellular compartments using GO and … |
| Anahtar Kelimeler |
| SARS-CoV-2 | miRNA | NFKB | JAK/STAT | TGFB |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 89 |
| Web of Science | 67 |