WGCNA was employed to identify modules associated with the synthetic periodontitis dataset.
<p>(A, B) Based on scale independence and average connectivity, β = 8 was considered the optimal soft-thresholding value. (C) Gene clustering tree with multiple partitioned modules. Different clusters are connected by different colors. (D) Heatmap of adjacency of feature genes.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , , , |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| _version_ | 1852017259678007296 |
|---|---|
| author | Zhifeng Wu (303016) |
| author2 | Fan Zhang (46132) Yuan Wang (14955) Chunjiang Liu (125011) Zhaokun Sun (19197309) Xiaoqi Tang (12996656) Liming Tang (2231494) |
| author2_role | author author author author author author |
| author_facet | Zhifeng Wu (303016) Fan Zhang (46132) Yuan Wang (14955) Chunjiang Liu (125011) Zhaokun Sun (19197309) Xiaoqi Tang (12996656) Liming Tang (2231494) |
| author_role | author |
| dc.creator.none.fl_str_mv | Zhifeng Wu (303016) Fan Zhang (46132) Yuan Wang (14955) Chunjiang Liu (125011) Zhaokun Sun (19197309) Xiaoqi Tang (12996656) Liming Tang (2231494) |
| dc.date.none.fl_str_mv | 2025-08-26T17:50:07Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0329592.g003 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/WGCNA_was_employed_to_identify_modules_associated_with_the_synthetic_periodontitis_dataset_/29991171 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biochemistry Microbiology Cell Biology Genetics Molecular Biology Immunology Biological Sciences not elsewhere classified Information Systems not elsewhere classified targeted drug prediction receiver operating characteristic conducted differential analysis abdominal aortic aneurysm expression network analysis external independent datasets ppi network analysis related module genes identified key genes ppi network candidate genes obtained datasets xlink "> validation confirmed ten drugs robustly associated positive correlations neutrophil infiltration machine learning intersection initially geo database bioinformatics approaches |
| dc.title.none.fl_str_mv | WGCNA was employed to identify modules associated with the synthetic periodontitis dataset. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>(A, B) Based on scale independence and average connectivity, β = 8 was considered the optimal soft-thresholding value. (C) Gene clustering tree with multiple partitioned modules. Different clusters are connected by different colors. (D) Heatmap of adjacency of feature genes.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_2e648f94962106986ac7a8bc2b20afb6 |
| identifier_str_mv | 10.1371/journal.pone.0329592.g003 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29991171 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | WGCNA was employed to identify modules associated with the synthetic periodontitis dataset.Zhifeng Wu (303016)Fan Zhang (46132)Yuan Wang (14955)Chunjiang Liu (125011)Zhaokun Sun (19197309)Xiaoqi Tang (12996656)Liming Tang (2231494)BiochemistryMicrobiologyCell BiologyGeneticsMolecular BiologyImmunologyBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedtargeted drug predictionreceiver operating characteristicconducted differential analysisabdominal aortic aneurysmexpression network analysisexternal independent datasetsppi network analysisrelated module genesidentified key genesppi networkcandidate genesobtained datasetsxlink ">validation confirmedten drugsrobustly associatedpositive correlationsneutrophil infiltrationmachine learningintersection initiallygeo databasebioinformatics approaches<p>(A, B) Based on scale independence and average connectivity, β = 8 was considered the optimal soft-thresholding value. (C) Gene clustering tree with multiple partitioned modules. Different clusters are connected by different colors. (D) Heatmap of adjacency of feature genes.</p>2025-08-26T17:50:07ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0329592.g003https://figshare.com/articles/figure/WGCNA_was_employed_to_identify_modules_associated_with_the_synthetic_periodontitis_dataset_/29991171CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/299911712025-08-26T17:50:07Z |
| spellingShingle | WGCNA was employed to identify modules associated with the synthetic periodontitis dataset. Zhifeng Wu (303016) Biochemistry Microbiology Cell Biology Genetics Molecular Biology Immunology Biological Sciences not elsewhere classified Information Systems not elsewhere classified targeted drug prediction receiver operating characteristic conducted differential analysis abdominal aortic aneurysm expression network analysis external independent datasets ppi network analysis related module genes identified key genes ppi network candidate genes obtained datasets xlink "> validation confirmed ten drugs robustly associated positive correlations neutrophil infiltration machine learning intersection initially geo database bioinformatics approaches |
| status_str | publishedVersion |
| title | WGCNA was employed to identify modules associated with the synthetic periodontitis dataset. |
| title_full | WGCNA was employed to identify modules associated with the synthetic periodontitis dataset. |
| title_fullStr | WGCNA was employed to identify modules associated with the synthetic periodontitis dataset. |
| title_full_unstemmed | WGCNA was employed to identify modules associated with the synthetic periodontitis dataset. |
| title_short | WGCNA was employed to identify modules associated with the synthetic periodontitis dataset. |
| title_sort | WGCNA was employed to identify modules associated with the synthetic periodontitis dataset. |
| topic | Biochemistry Microbiology Cell Biology Genetics Molecular Biology Immunology Biological Sciences not elsewhere classified Information Systems not elsewhere classified targeted drug prediction receiver operating characteristic conducted differential analysis abdominal aortic aneurysm expression network analysis external independent datasets ppi network analysis related module genes identified key genes ppi network candidate genes obtained datasets xlink "> validation confirmed ten drugs robustly associated positive correlations neutrophil infiltration machine learning intersection initially geo database bioinformatics approaches |