Identification and Classification of Small RNAs in Transcriptome Sequence DataD. Langenberger1, C.I. Bermudez-Santana1,2, P.F. Stadler1,3, S. Hoffmann1 1University Leipzig, Chair of Bioinformatics & Interdisciplinary Center for Bioinformatics, Haertelstrasse 16-18, D-04107 Leipzig, Germany; 2Department of Biology, Universidad Nacional de Colombia, Carrera 45, No. 26-85, Edificio Uriel Gutierrez, D.C., Colombia; 3Max-Planck-Insitute for Mathematics in Sciences (MPI-MIS), Inselstrasse 22, D-04103 Leipzig, Germany Email: steve@bioinf.uni-leipzig.de Pacific Symposium on Biocomputing 15:80-87(2010) |
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AbstractCurrent methods for high throughput sequencing (HTS) for the first time offer the opportunity to investigate the entire transcriptome in an essentially unbiased way. In many species, small non-coding RNAs with specific secondary structures constitute a significant part of the transcriptome. Some of these RNA classes, in particular microRNAs and snoRNAs, undergo maturation processes that lead to the production of shorter RNAs. After mapping the sequences to the reference genome specific patterns of short reads can be observed. These read patterns seem to reflect the processing and thus are specific for the RNA transcripts of which they are derived from. We explore here the potential of short read sequence data in the classification and identification of non-coding RNAs. | |
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