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Exploring ncRNAs in Alzheimer’s disease by miRMaster
| Content Provider | Semantic Scholar |
|---|---|
| Author | Fehlmann, Tobias Meese, Eckart Keller, Andreas |
| Copyright Year | 2017 |
| Abstract | Circulating biomarkers for the diagnosis of Alzheimer’s Disease (AD) such as amyloid-β levels are already applied in clinical care. New markers, especially marker panels that can be measured from blood and specifically focusing at early diagnosis, are under development [1]. Previously, we published miRNA signatures in Alzheimer’s Disease that have been discovered by high-throughput sequencing (also denoted as next-generation sequencing, NGS) [2, 3]. These studies focused on the quantification of known human miRNAs. Sequencing the fraction of all small RNAs in a specimen, however, allows not only for investigating canonical miRNAs but also enables prediction of new miRNAs, isoforms of miRNAs and even provides first insights in other RNA types. We developed a tool for the comprehensive analysis of small non-coding RNAs, primary miRNAs, starting from NGS raw data. Our web-based program miRMaster is free for academic users: www.ccb.uni-saarland.de/ mirmaster. Beyond the core functionality of analyzing known miRNAs, predicting isomiRs, discovery of mutations in miRNAs and identifying new miRNAs, we |
| Starting Page | 3771 |
| Ending Page | 3772 |
| Page Count | 2 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&op=download&page=article&path%5B%5D=14054&path%5B%5D=44809 |
| PubMed reference number | 28030833v1 |
| Alternate Webpage(s) | https://doi.org/10.18632/oncotarget.14054 |
| DOI | 10.18632/oncotarget.14054 |
| Journal | Oncotarget |
| Volume Number | 8 |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Alzheimer's Disease Biological Markers Biopolymer Sequencing CDISC SEND Biospecimens Terminology Massively-Parallel Sequencing MicroRNAs Mutation Protein Isoforms Quantitation RNA Scientific Publication |
| Content Type | Text |
| Resource Type | Article |