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dc.contributor.author
Helmuth, Jo A.
dc.contributor.author
Paul, Grégory
dc.contributor.author
Sbalzarini, Ivo F.
dc.date.accessioned
2018-09-04T14:38:14Z
dc.date.available
2017-06-09T05:23:57Z
dc.date.available
2018-09-04T14:38:14Z
dc.date.issued
2010-07
dc.identifier.issn
1471-2105
dc.identifier.other
10.1186/1471-2105-11-372
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/22277
dc.identifier.doi
10.3929/ethz-b-000022277
dc.description.abstract
Background Sub-cellular structures interact in numerous direct and indirect ways in order to fulfill cellular functions. While direct molecular interactions crucially depend on spatial proximity, other interactions typically result in spatial correlations between the interacting structures. Such correlations are the target of microscopy-based co-localization analysis, which can provide hints of potential interactions. Two complementary approaches to co-localization analysis can be distinguished: intensity correlation methods capitalize on pattern discovery, whereas object-based methods emphasize detection power. Results We first reinvestigate the classical co-localization measure in the context of spatial point pattern analysis. This allows us to unravel the set of implicit assumptions inherent to this measure and to identify potential confounding factors commonly ignored. We generalize object-based co-localization analysis to a statistical framework involving spatial point processes. In this framework, interactions are understood as position co-dependencies in the observed localization patterns. The framework is based on a model of effective pairwise interaction potentials and the specification of a null hypothesis for the expected pattern in the absence of interaction. Inferred interaction potentials thus reflect all significant effects that are not explained by the null hypothesis. Our model enables the use of a wealth of well-known statistical methods for analyzing experimental data, as demonstrated on synthetic data and in a case study considering virus entry into live cells. We show that the classical co-localization measure typically under-exploits the information contained in our data. Conclusions We establish a connection between co-localization and spatial interaction of sub-cellular structures by formulating the object-based interaction analysis problem in a spatial statistics framework based on nearest-neighbor distance distributions. We provide generic procedures for inferring interaction strengths and quantifying their relative statistical significance from sets of discrete objects as provided by image analysis methods. Within our framework, an interaction potential can either refer to a phenomenological or a mechanistic model of a physico-chemical interaction process. This increased flexibility in designing and testing different hypothetical interaction models can be used to quantify the parameters of a specific interaction model or may catalyze the discovery of functional relations.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/2.0/
dc.subject
Monte Carlo
en_US
dc.subject
Enhance Green Fluorescent Protein
en_US
dc.subject
Interaction Strength
en_US
dc.subject
Near Neighbor
en_US
dc.subject
Distance Threshold
en_US
dc.title
Beyond co-localization: inferring spatial interactions between sub-cellular structures from microscopy images
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 2.0 Generic
ethz.journal.title
BMC Bioinformatics
ethz.journal.volume
11
en_US
ethz.pages.start
372
en_US
ethz.size
12 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.nebis
004240301
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
03749 - Sbalzarini, Ivo F.
en_US
ethz.leitzahl.certified
03749 - Sbalzarini, Ivo F.
ethz.date.deposited
2017-06-09T05:24:16Z
ethz.source
ECIT
ethz.identifier.importid
imp59364cfc89f4c58852
ethz.ecitpid
pub:37098
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-13T07:52:18Z
ethz.rosetta.lastUpdated
2021-02-15T01:31:54Z
ethz.rosetta.versionExported
true
ethz.COinS
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