Gutenberg Open Science: A computational method for studying the relation between alternative splicing and DNA methylation

Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-7983

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DC Field	Value	Language
dc.contributor.author	Zheng, Zejun	-
dc.contributor.author	Wei, Xiaona	-
dc.contributor.author	Hildebrandt, Andreas	-
dc.contributor.author	Schmidt, Bertil	-
dc.date.accessioned	2022-10-13T09:34:35Z	-
dc.date.available	2022-10-13T09:34:35Z	-
dc.date.issued	2016
dc.identifier.uri	https://openscience.ub.uni-mainz.de/handle/20.500.12030/7998	-
dc.description.abstract	Alternative splicing is an important mechanism in eukaryotes that expands the transcriptome and proteome significantly. It plays an important role in a number of biological processes. Understanding its regulation is hence an important challenge. Recently, increasing evidence has been collected that supports an involvement of intragenic DNA methylation in the regulation of alternative splicing. The exact mechanisms of regulation, however, are largely unknown, and speculated to be complex: different methylation profiles might exist, each of which could be associated with a different regulation mechanism. We present a computational technique that is able to determine such stable methylation patterns and allows to correlate these patterns with inclusion propensity of exons. Pattern detection is based on dynamic time warping (DTW) of methylation profiles, a sophisticated similarity measure for signals that can be non-trivially transformed. We design a flexible self-organizing map approach to pattern grouping. Exemplary application on available data sets indicates that stable patterns which correlate non-trivially with exon inclusion do indeed exist. To improve the reliability of these predictions, further studies on larger data sets will be required. We have thus taken great care that our software runs efficiently on modern hardware, so that it can support future studies on large-scale data sets.	en_GB
dc.description.sponsorship	DFG, Open Access-Publizieren Universität Mainz / Universitätsmedizin	de
dc.language.iso	eng	de
dc.rights	CC BY	*
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/	*
dc.subject.ddc	570 Biowissenschaften	de_DE
dc.subject.ddc	570 Life sciences	en_GB
dc.title	A computational method for studying the relation between alternative splicing and DNA methylation	en_GB
dc.type	Zeitschriftenaufsatz	de
dc.identifier.doi	http://doi.org/10.25358/openscience-7983	-
jgu.type.dinitype	article	en_GB
jgu.type.version	Published version	de
jgu.type.resource	Text	de
jgu.organisation.department	FB 08 Physik, Mathematik u. Informatik	de
jgu.organisation.number	7940	-
jgu.organisation.name	Johannes Gutenberg-Universität Mainz	-
jgu.rights.accessrights	openAccess	-
jgu.journal.title	Nucleic acids research	de
jgu.journal.volume	44	de
jgu.journal.issue	2	de
jgu.pages.alternative	e19	de
jgu.publisher.year	2016	-
jgu.publisher.name	Oxford Univ. Press	de
jgu.publisher.place	Oxford	de
jgu.publisher.uri	http://dx.doi.org/10.1093/nar/gkv906	de
jgu.publisher.issn	1362-4962	de
jgu.publisher.issn	0305-1048	de
jgu.organisation.place	Mainz	-
jgu.subject.ddccode	570	de
opus.date.modified	2018-09-06T10:16:02Z
opus.subject.dfgcode	00-000
opus.organisation.string	FB 08: Physik, Mathematik und Informatik: Institut für Informatik	de_DE
opus.identifier.opusid	56551
opus.institute.number	0805
opus.metadataonly	false
opus.type.contenttype	Keine	de_DE
opus.type.contenttype	None	en_EN
opus.affiliated	Hildebrandt, Andreas
opus.affiliated	Schmidt, Bertil
jgu.publisher.doi	10.1093/nar/gkv906	de
jgu.organisation.ror	https://ror.org/023b0x485	-
Appears in collections:	DFG-OA-Publizieren (2012 - 2017)

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