Universität zu Köln

Machne, Rainer ORCID: 0000-0002-1274-5099, Murray, Douglas B. and Stadler, Peter F. ORCID: 0000-0002-5016-5191 (2017). Similarity-Based Segmentation of Multi-Dimensional Signals. Sci Rep, 7. LONDON: NATURE PUBLISHING GROUP. ISSN 2045-2322

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Abstract

The segmentation of time series and genomic data is a common problem in computational biology. With increasingly complex measurement procedures individual data points are often not just numbers or simple vectors in which all components are of the same kind. Analysis methods that capitalize on slopes in a single real-valued data track or that make explicit use of the vectorial nature of the data are not applicable in such scenaria. We develop here a framework for segmentation in arbitrary data domains that only requires a minimal notion of similarity. Using unsupervised clustering of (a sample of) the input yields an approximate segmentation algorithm that is efficient enough for genome-wide applications. As a showcase application we segment a time-series of transcriptome sequencing data from budding yeast, in high temporal resolution over ca. 2.5 cycles of the short-period respiratory oscillation. The algorithm is used with a similarity measure focussing on periodic expression profiles across the metabolic cycle rather than coverage per time point.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Machne, Rainer UNSPECIFIED orcid.org/0000-0002-1274-5099 UNSPECIFIED Murray, Douglas B. UNSPECIFIED UNSPECIFIED UNSPECIFIED Stadler, Peter F. UNSPECIFIED orcid.org/0000-0002-5016-5191 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-217415
DOI:	10.1038/s41598-017-12401-8
Journal or Publication Title:	Sci Rep
Volume:	7
Date:	2017
Publisher:	NATURE PUBLISHING GROUP
Place of Publication:	LONDON
ISSN:	2045-2322
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language METRIC-SPACES; SACCHAROMYCES-CEREVISIAE; CHROMATIN STATES; BUDDING YEAST; GENOME; TRANSCRIPTION; RNA; DISCOVERY; DNA; ANNOTATION Multiple languages Multidisciplinary Sciences Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/21741