Details zur Publikation

Referenztyp Buchkapitel
DOI / URL Link
Titel (primär) Bioinformatics for RNomics
Titel (sekundär) Bioinformatics for Omics data
Autor Reiche, K.; Schutt, K.; Boll, K.; Horn, F.; Hackermüller, J.;
Herausgeber Mayer, B.;
Journal / Serie Methods in Molecular Biology
Erscheinungsjahr 2011
Department PROTEOM;
Band/Volume 719
Sprache englisch;
Keywords RNomics; Non-coding RNA; ncRNA; Transcriptome; Bioinformatics; Regulatory RNA
Abstract
Rapid improvements in high-throughput experimental technologies make it nowadays possible to study the expression, as well as changes in expression, of whole transcriptomes under different environmental conditions in a detailed view. We describe current approaches to identify genome-wide functional RNA transcripts (experimentally as well as computationally), and focus on computational methods that may be utilized to disclose their function. While genome databases offer a wealth of information about known and putative functions for protein-coding genes, functional information for novel non-coding RNA genes is almost nonexistent. This is mainly explained by the lack of established software tools to efficiently reveal the function and evolutionary origin of non-coding RNA genes. Here, we describe in detail computational approaches one may follow to annotate and classify an RNA transcript.
ID 12938
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=12938
Reiche, K., Schutt, K., Boll, K., Horn, F., Hackermüller, J. (2011):
Bioinformatics for RNomics
In: Mayer, B. (ed.)
Bioinformatics for Omics data
Methods in Molecular Biology 719
Humana Press, p. 299 - 330