About: Towards a computational model for −1 eukaryotic frameshifting sites

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Towards a computational model for −1 eukaryotic frameshifting sites
Creator	Bekaert, Michaël Rousset, Jean-Pierre Bidou, Laure Denise, Alain Duchateau-Nguyen, Guillemette Forest, Jean-Paul Froidevaux, Christine Hatin, Isabelle Termier, Michel
Source	Medline; PMC
abstract	Motivation: Unconventional decoding events are now well acknowledged, but not yet well formalized. In this study, we present a bioinformatics analysis of eukaryotic −1 frameshifting, in order to model this event. Results: A consensus model has already been established for −1 frameshifting sites. Our purpose here is to provide new constraints which make the model more precise. We show how a machine learning approach can be used to refine the current model. We identify new properties that may be involved in frameshifting. Each of the properties found was experimentally validated. Initially, we identify features of the overall model that are to be simultaneously satisfied. We then focus on the following two components: the spacer and the slippery sequence. As a main result, we point out that the identity of the primary structure of the so-called spacer is of great importance. Availability: Sequences of the oligonucleotides in the functional tests are available at http://www.igmors.u-psud.fr/rousset/bioinformatics/ Contact: bekaert@igmors.u-psud.frjpforest@lri.frchris@lri.fr
has issue date	2003-02-12(xsd:dateTime)
bibo:doi	10.1093/bioinformatics/btf868
bibo:pmid	12584117
has license	no-cc
sha1sum (hex)	4cc918298766103c7744712a7aeddd1fe3454304
schema:url	https://doi.org/10.1093/bioinformatics/btf868
resource representing a document's title	Towards a computational model for −1 eukaryotic frameshifting sites
has PubMed Central identifier	PMC7109833
has PubMed identifier	12584117
schema:publication	Bioinformatics
resource representing a document's body	covid:4cc918298766103c7744712a7aeddd1fe3454304#body_text
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