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dc.contributor.authorNawaz, S
dc.contributor.authorYuan, Y
dc.date.accessioned2016-10-05T14:53:44Z
dc.date.issued2016-09
dc.identifier.citationCancer letters, 2016, 380 (1), pp. 296 - 303
dc.identifier.issn0304-3835
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/161
dc.identifier.eissn1872-7980
dc.identifier.doi10.1016/j.canlet.2015.11.018
dc.description.abstractTumors are evolving ecosystems where cancer subclones and the microenvironment interact. This is analogous to interaction dynamics between species in their natural habitats, which is a prime area of study in ecology. Spatial statistics are frequently used in ecological studies to infer complex relations including predator-prey, resource dependency and co-evolution. Recently, the emerging field of computational pathology has enabled high-throughput spatial analysis by using image processing to identify different cell types and their locations within histological tumor samples. We discuss how these data may be analyzed with spatial statistics used in ecology to reveal patterns and advance our understanding of ecological interactions occurring among cancer cells and their microenvironment.
dc.formatPrint-Electronic
dc.format.extent296 - 303
dc.languageeng
dc.language.isoeng
dc.subjectAnimals
dc.subjectHumans
dc.subjectBreast Neoplasms
dc.subjectImage Interpretation, Computer-Assisted
dc.subjectBiopsy
dc.subjectPrognosis
dc.subjectModels, Statistical
dc.subjectPredictive Value of Tests
dc.subjectPathology
dc.subjectPhenotype
dc.subjectTime Factors
dc.subjectPattern Recognition, Automated
dc.subjectFemale
dc.subjectHigh-Throughput Screening Assays
dc.subjectTumor Microenvironment
dc.titleComputational pathology: Exploring the spatial dimension of tumor ecology.
dc.typeJournal Article
dcterms.dateAccepted2015-11-10
rioxxterms.versionofrecord10.1016/j.canlet.2015.11.018
rioxxterms.licenseref.startdate2016-09
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfCancer letters
pubs.issue1
pubs.notesNo embargo
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Computational Pathology & Integrated Genomics
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Computational Pathology & Integrated Genomics
pubs.publication-statusPublished
pubs.volume380en_US
pubs.embargo.termsNo embargo
icr.researchteamComputational Pathology & Integrated Genomicsen_US
dc.contributor.icrauthorNawaz, Sidraen
dc.contributor.icrauthorYuan, Yinyinen


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