UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.

<p>The diagram reveals limited consensus among methods, with our method pinpointing a distinct subset of genes not commonly selected by other approaches. This indicates the uniqueness of our ranking strategy and its potential to uncover novel biomarkers in GAC.</p> <p>(EPS)</p&g...

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Huvudupphovsman: Fatemeh Keikha (20917848) (author)
Övriga upphovsmän: Chuanyuan Wang (22676721) (author), Zhixia Yang (3180567) (author), Zhi-Ping Liu (149304) (author)
Publicerad: 2025
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author Fatemeh Keikha (20917848)
author2 Chuanyuan Wang (22676721)
Zhixia Yang (3180567)
Zhi-Ping Liu (149304)
author2_role author
author
author
author_facet Fatemeh Keikha (20917848)
Chuanyuan Wang (22676721)
Zhixia Yang (3180567)
Zhi-Ping Liu (149304)
author_role author
dc.creator.none.fl_str_mv Fatemeh Keikha (20917848)
Chuanyuan Wang (22676721)
Zhixia Yang (3180567)
Zhi-Ping Liu (149304)
dc.date.none.fl_str_mv 2025-11-24T18:36:39Z
dc.identifier.none.fl_str_mv 10.1371/journal.pcbi.1013743.s011
dc.relation.none.fl_str_mv https://figshare.com/articles/figure/UpSet_diagram_illustrating_the_overlap_of_DNBs_selected_by_our_method_and_top-ranked_genes_by_the_13_baseline_centrality-based_ranking_algorithms_/30697954
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Medicine
Genetics
Biotechnology
Cancer
Infectious Diseases
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
wasserstein optimal transport
real world dataset
quantified via gromov
enhancing diagnostic precision
dynamic network index
deep neural network
ablation studies confirm
regulatory role transitions
gene regulatory networks
combining regulatory rewiring
analyzing disease evolution
temporal expression dynamics
reflect dynamic changes
neglecting structural rewiring
multilayer network models
modeling disease progression
state alignment provides
understanding cancer progression
state graph alignment
disease state classification
state specific biomarkers
disease progression
state alignment
specific expression
multilayer graph
cancer progression
disease state
regulatory variability
regulatory roles
structural shifts
significant changes
prioritized biomarkers
classification accuracy
state single
xlink ">
topological features
synthetic simulated
ranked using
powerful strategy
overall performance
meaningful shifts
gats ),
gastric adenocarcinoma
gac ),
framework designed
findings suggest
dni ),
distinct layer
contextualized embeddings
cell data
dc.title.none.fl_str_mv UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.
dc.type.none.fl_str_mv Image
Figure
info:eu-repo/semantics/publishedVersion
image
description <p>The diagram reveals limited consensus among methods, with our method pinpointing a distinct subset of genes not commonly selected by other approaches. This indicates the uniqueness of our ranking strategy and its potential to uncover novel biomarkers in GAC.</p> <p>(EPS)</p>
eu_rights_str_mv openAccess
id Manara_4f976420f99517374df70fce8c50a8a3
identifier_str_mv 10.1371/journal.pcbi.1013743.s011
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/30697954
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.Fatemeh Keikha (20917848)Chuanyuan Wang (22676721)Zhixia Yang (3180567)Zhi-Ping Liu (149304)MedicineGeneticsBiotechnologyCancerInfectious DiseasesBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedwasserstein optimal transportreal world datasetquantified via gromovenhancing diagnostic precisiondynamic network indexdeep neural networkablation studies confirmregulatory role transitionsgene regulatory networkscombining regulatory rewiringanalyzing disease evolutiontemporal expression dynamicsreflect dynamic changesneglecting structural rewiringmultilayer network modelsmodeling disease progressionstate alignment providesunderstanding cancer progressionstate graph alignmentdisease state classificationstate specific biomarkersdisease progressionstate alignmentspecific expressionmultilayer graphcancer progressiondisease stateregulatory variabilityregulatory rolesstructural shiftssignificant changesprioritized biomarkersclassification accuracystate singlexlink ">topological featuressynthetic simulatedranked usingpowerful strategyoverall performancemeaningful shiftsgats ),gastric adenocarcinomagac ),framework designedfindings suggestdni ),distinct layercontextualized embeddingscell data<p>The diagram reveals limited consensus among methods, with our method pinpointing a distinct subset of genes not commonly selected by other approaches. This indicates the uniqueness of our ranking strategy and its potential to uncover novel biomarkers in GAC.</p> <p>(EPS)</p>2025-11-24T18:36:39ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pcbi.1013743.s011https://figshare.com/articles/figure/UpSet_diagram_illustrating_the_overlap_of_DNBs_selected_by_our_method_and_top-ranked_genes_by_the_13_baseline_centrality-based_ranking_algorithms_/30697954CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/306979542025-11-24T18:36:39Z
spellingShingle UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.
Fatemeh Keikha (20917848)
Medicine
Genetics
Biotechnology
Cancer
Infectious Diseases
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
wasserstein optimal transport
real world dataset
quantified via gromov
enhancing diagnostic precision
dynamic network index
deep neural network
ablation studies confirm
regulatory role transitions
gene regulatory networks
combining regulatory rewiring
analyzing disease evolution
temporal expression dynamics
reflect dynamic changes
neglecting structural rewiring
multilayer network models
modeling disease progression
state alignment provides
understanding cancer progression
state graph alignment
disease state classification
state specific biomarkers
disease progression
state alignment
specific expression
multilayer graph
cancer progression
disease state
regulatory variability
regulatory roles
structural shifts
significant changes
prioritized biomarkers
classification accuracy
state single
xlink ">
topological features
synthetic simulated
ranked using
powerful strategy
overall performance
meaningful shifts
gats ),
gastric adenocarcinoma
gac ),
framework designed
findings suggest
dni ),
distinct layer
contextualized embeddings
cell data
status_str publishedVersion
title UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.
title_full UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.
title_fullStr UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.
title_full_unstemmed UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.
title_short UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.
title_sort UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms.
topic Medicine
Genetics
Biotechnology
Cancer
Infectious Diseases
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
wasserstein optimal transport
real world dataset
quantified via gromov
enhancing diagnostic precision
dynamic network index
deep neural network
ablation studies confirm
regulatory role transitions
gene regulatory networks
combining regulatory rewiring
analyzing disease evolution
temporal expression dynamics
reflect dynamic changes
neglecting structural rewiring
multilayer network models
modeling disease progression
state alignment provides
understanding cancer progression
state graph alignment
disease state classification
state specific biomarkers
disease progression
state alignment
specific expression
multilayer graph
cancer progression
disease state
regulatory variability
regulatory roles
structural shifts
significant changes
prioritized biomarkers
classification accuracy
state single
xlink ">
topological features
synthetic simulated
ranked using
powerful strategy
overall performance
meaningful shifts
gats ),
gastric adenocarcinoma
gac ),
framework designed
findings suggest
dni ),
distinct layer
contextualized embeddings
cell data