Detailansicht
In silico modelling of RNA-RNA dimer and its application for rational siRNA design and ncRNA target search
Hakim Tafer
Art der Arbeit
Dissertation
Universität
Universität Wien
Fakultät
Fakultät für Physik
Betreuer*in
Ivo Hofacker
DOI
10.25365/thesis.16273
URN
urn:nbn:at:at-ubw:1-29933.56547.650853-1
Link zu u:search
(Print-Exemplar eventuell in Bibliothek verfügbar)
Abstracts
Abstract
(Deutsch)
Non-protein coding region, which constitutes 98.5% of the human genome, were long
depreciated as evolutive relict. It is only recently that the biological relevance of
the non-coding RNAs associated with these non-coding regions was recognized. The
development of experimental and bioinformatical methods aimed at detecting these
non-coding RNAs (ncRNAs) lead to the discovery of more than 29,000,000 sequences,
grouped into more than 1300 families.
More often than not these ncRNAs function by binding to other RNAs, either pro-
tein coding or non-protein coding. Compared to the number of tools to detect and
classify ncRNAs, the number of tools to search for putative RNA binding partners
is negligible. This leads to the actual situation where the function of the majority of
the annotated ncRNAs genes is completely unknown.
The aim of this work is to assess the function of different families of ncRNAs by
developing new algorithms and methods to study RNA-RNA interactions. These new
methods are extensions of RNA-folding algorithms applied to the problem of RNA-
RNA interactions. Depending on the class of ncRNA studied, different methods were
developed and tested.
This work shows that the development of RNA-folding algorithms to study RNA-
RNA interactions is a promising way to functionally annotate ncRNAs. Still other
factors like RNA-proteins interaction, RNA-concentration or RNA-expression, play
an important role in the process of RNA hybridization and will have to be taken
into account in future works in order to achieve reliable prediction of RNA binding
partners.
Abstract
(Englisch)
Non-protein coding region, which constitutes 98.5% of the human genome, were long
depreciated as evolutive relict. It is only recently that the biological relevance of
the non-coding RNAs associated with these non-coding regions was recognized. The
development of experimental and bioinformatical methods aimed at detecting these
non-coding RNAs (ncRNAs) lead to the discovery of more than 29,000,000 sequences,
grouped into more than 1300 families.
More often than not these ncRNAs function by binding to other RNAs, either pro-
tein coding or non-protein coding. Compared to the number of tools to detect and
classify ncRNAs, the number of tools to search for putative RNA binding partners
is negligible. This leads to the actual situation where the function of the majority of
the annotated ncRNAs genes is completely unknown.
The aim of this work is to assess the function of different families of ncRNAs by
developing new algorithms and methods to study RNA-RNA interactions. These new
methods are extensions of RNA-folding algorithms applied to the problem of RNA-
RNA interactions. Depending on the class of ncRNA studied, different methods were
developed and tested.
This work shows that the development of RNA-folding algorithms to study RNA-
RNA interactions is a promising way to functionally annotate ncRNAs. Still other
factors like RNA-proteins interaction, RNA-concentration or RNA-expression, play
an important role in the process of RNA hybridization and will have to be taken
into account in future works in order to achieve reliable prediction of RNA binding
partners.
Schlagwörter
Schlagwörter
(Englisch)
RNA RNA-RNA interaktion siRNA RNA secondary structure
Schlagwörter
(Deutsch)
RNS RNS-RNS Wechselwirkung siRNA RNS-Sekundaerstruktur
Autor*innen
Hakim Tafer
Haupttitel (Englisch)
In silico modelling of RNA-RNA dimer and its application for rational siRNA design and ncRNA target search
Publikationsjahr
2011
Umfangsangabe
191, 2 S. : Ill.
Sprache
Englisch
Beurteiler*innen
David Kreil ,
Andrew Torda
Klassifikation
30 Naturwissenschaften allgemein > 30.00 Naturwissenschaften allgemein: Allgemeines
AC Nummer
AC08824552
Utheses ID
14592
Studienkennzahl
UA | 791 | 411 | |