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A graph theoretical approach to data fusion

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Title: A graph theoretical approach to data fusion
Authors: Zurauskiene, J
Kirk, PDW
Stumpf, MPH
Item Type: Journal Article
Issue Date: 18-Mar-2016
Date of Acceptance: 18-Mar-2016
URI: http://hdl.handle.net/10044/1/33803
DOI: http://dx.doi.org/10.1515/sagmb-2016-0016
ISSN: 1544-6115
Publisher: De Gruyter
Start Page: 107
End Page: 122
Journal / Book Title: Statistical Applications in Genetics and Molecular Biology
Volume: 15
Issue: 2
Copyright Statement: © 2016, Michael P.H. Stumpf et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Sponsor/Funder: The Leverhulme Trust
Human Frontier Science Program
Biotechnology and Biological Sciences Research Council (BBSRC)
Funder's Grant Number: F/07 058/BP
RGP0061/2011
BB/K017284/1
Keywords: Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Biochemistry & Molecular Biology
Mathematical & Computational Biology
Statistics & Probability
Mathematics
clustering
data integration
functional genomics
graph-theoretic methods
INCLUSION-BODY MYOSITIS
PROTEIN-INTERACTION NETWORKS
MITOTIC CELL-CYCLE
BIOLOGICAL NETWORKS
DATA INTEGRATION
GENOMIC DATA
COMPLEXES
INFERENCE
BREAST
VISUALIZATION
Bioinformatics
01 Mathematical Sciences
06 Biological Sciences
Publication Status: Published
Open Access location: http://www.degruyter.com/view/j/sagmb.2016.15.issue-2/sagmb-2016-0016/sagmb-2016-0016.xml
Appears in Collections:Faculty of Natural Sciences