In silico search for secondary structures in p53 target genes using R/Bioconductor

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Publikace nespadá pod Fakultu sportovních studií, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
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BRÁZDOVÁ Marie MARTÍNEK Tomáš LEXA Matej

Rok publikování 2013
Druh Článek ve sborníku
Konference ITAT 2013: Information Technologies - Applications and Theory (Workshops, Posters, and Tutorials)
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www https://www.researchgate.net/publication/254257375_In_silico_search_for_secondary_structures_in_p53_target_genes_using_RBioconductor?ev=prf_pub
Obor Informatika
Klíčová slova R/bioconductor; p53; bioinformatika; analýza sekvence DNA
Popis p53 is a well-known transcription factor and tumor suppressor, regulating among other processes, the commitment of cells to apoptosis and DNA repair. p53 mutants are often found in cancers of different kinds, ei- ther as mutant or misregulated p53. p53 is involved in many other processes and we currently do not understand the full range of its functions. It is known to recognize the p53con sequence by its specific DNA-binding domain (DBD). It is also known to bind DNA non-specifically. This binding has been shown to involve superhelical DNA, more specifically, cruciform, triplex and quadruplex struc- tures. In our laboratories we were intrigued by the possi- ble interplay between non-canonical DNA structure bind- ing and regular p53con binding. In an attempt to clarify this interplay and discover suitable candidate genes for fur- ther study, we carried out an in silico study on the human genome. We identified all the occurences of potential cru- ciform DNA, triplex DNA, quadruplex DNA and p53con recognition sequences in +/-40000 bp regions of known genes. We analyzed this data for statistically significant patterns and combinations of patterns using a small set of available R/Bioconductor packages. This paper describes the computational pipeline designed for this type of stud- ies. We also show preliminary results for selected human sequences.
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