The proportion of target pathway genes for Hermetia illucens experiment.
<p>The proportion of target pathway genes for Hermetia illucens experiment.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
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| _version_ | 1852022720706904064 |
|---|---|
| author | Rui Miao (1592461) |
| author2 | Hao-Yang Yu (8219421) Bing-Jie Zhong (20721810) Hong-Xia Sun (1282485) Qiang Xia (289073) |
| author2_role | author author author author |
| author_facet | Rui Miao (1592461) Hao-Yang Yu (8219421) Bing-Jie Zhong (20721810) Hong-Xia Sun (1282485) Qiang Xia (289073) |
| author_role | author |
| dc.creator.none.fl_str_mv | Rui Miao (1592461) Hao-Yang Yu (8219421) Bing-Jie Zhong (20721810) Hong-Xia Sun (1282485) Qiang Xia (289073) |
| dc.date.none.fl_str_mv | 2025-02-13T18:47:58Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pcbi.1012773.t002 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/The_proportion_of_target_pathway_genes_for_Hermetia_illucens_experiment_/28413198 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Microbiology Genetics Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified unsupervised baseline models network weighting module initially construct experiments important insect resource experimental results demonstrate existing models assume researchers usually pay hermetia illucens </ weighted gene network gene selection capabilities pathway quantitative information pathway enrichment region innovative unsupervised model three major challenges ablation experiments validate available genomic data genomic data analysis espca model code growth genome dataset genomic data limits researchers genome analysis known gene gene probes gene probe superior pathway model performance espca model sparse pca serious problem rich regions representative supervised priori weight paper presents genes located effectively addressing awge_espca </ artificial intelligence also provide also integrate adaptive regularizer |
| dc.title.none.fl_str_mv | The proportion of target pathway genes for Hermetia illucens experiment. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>The proportion of target pathway genes for Hermetia illucens experiment.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_5bd00be8260decbf85b4a2cd2ffbf24a |
| identifier_str_mv | 10.1371/journal.pcbi.1012773.t002 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28413198 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | The proportion of target pathway genes for Hermetia illucens experiment.Rui Miao (1592461)Hao-Yang Yu (8219421)Bing-Jie Zhong (20721810)Hong-Xia Sun (1282485)Qiang Xia (289073)MicrobiologyGeneticsScience PolicyEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedunsupervised baseline modelsnetwork weighting moduleinitially construct experimentsimportant insect resourceexperimental results demonstrateexisting models assumeresearchers usually payhermetia illucens </weighted gene networkgene selection capabilitiespathway quantitative informationpathway enrichment regioninnovative unsupervised modelthree major challengesablation experiments validateavailable genomic datagenomic data analysisespca model codegrowth genome datasetgenomic datalimits researchersgenome analysisknown genegene probesgene probesuperior pathwaymodel performanceespca modelsparse pcaserious problemrich regionsrepresentative supervisedpriori weightpaper presentsgenes locatedeffectively addressingawge_espca </artificial intelligencealso providealso integrateadaptive regularizer<p>The proportion of target pathway genes for Hermetia illucens experiment.</p>2025-02-13T18:47:58ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pcbi.1012773.t002https://figshare.com/articles/dataset/The_proportion_of_target_pathway_genes_for_Hermetia_illucens_experiment_/28413198CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/284131982025-02-13T18:47:58Z |
| spellingShingle | The proportion of target pathway genes for Hermetia illucens experiment. Rui Miao (1592461) Microbiology Genetics Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified unsupervised baseline models network weighting module initially construct experiments important insect resource experimental results demonstrate existing models assume researchers usually pay hermetia illucens </ weighted gene network gene selection capabilities pathway quantitative information pathway enrichment region innovative unsupervised model three major challenges ablation experiments validate available genomic data genomic data analysis espca model code growth genome dataset genomic data limits researchers genome analysis known gene gene probes gene probe superior pathway model performance espca model sparse pca serious problem rich regions representative supervised priori weight paper presents genes located effectively addressing awge_espca </ artificial intelligence also provide also integrate adaptive regularizer |
| status_str | publishedVersion |
| title | The proportion of target pathway genes for Hermetia illucens experiment. |
| title_full | The proportion of target pathway genes for Hermetia illucens experiment. |
| title_fullStr | The proportion of target pathway genes for Hermetia illucens experiment. |
| title_full_unstemmed | The proportion of target pathway genes for Hermetia illucens experiment. |
| title_short | The proportion of target pathway genes for Hermetia illucens experiment. |
| title_sort | The proportion of target pathway genes for Hermetia illucens experiment. |
| topic | Microbiology Genetics Science Policy Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified unsupervised baseline models network weighting module initially construct experiments important insect resource experimental results demonstrate existing models assume researchers usually pay hermetia illucens </ weighted gene network gene selection capabilities pathway quantitative information pathway enrichment region innovative unsupervised model three major challenges ablation experiments validate available genomic data genomic data analysis espca model code growth genome dataset genomic data limits researchers genome analysis known gene gene probes gene probe superior pathway model performance espca model sparse pca serious problem rich regions representative supervised priori weight paper presents genes located effectively addressing awge_espca </ artificial intelligence also provide also integrate adaptive regularizer |