Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-7983
Authors: Zheng, Zejun
Wei, Xiaona
Hildebrandt, Andreas
Schmidt, Bertil
Title: A computational method for studying the relation between alternative splicing and DNA methylation
Online publication date: 13-Oct-2022
Year of first publication: 2016
Language: english
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.
DDC: 570 Biowissenschaften
570 Life sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 08 Physik, Mathematik u. Informatik
Place: Mainz
ROR: https://ror.org/023b0x485
DOI: http://doi.org/10.25358/openscience-7983
Version: Published version
Publication type: Zeitschriftenaufsatz
License: CC BY
Information on rights of use: https://creativecommons.org/licenses/by/4.0/
Journal: Nucleic acids research
44
2
Pages or article number: e19
Publisher: Oxford Univ. Press
Publisher place: Oxford
Issue date: 2016
ISSN: 1362-4962
0305-1048
Publisher URL: http://dx.doi.org/10.1093/nar/gkv906
Publisher DOI: 10.1093/nar/gkv906
Appears in collections:DFG-OA-Publizieren (2012 - 2017)

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