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pmid:36544902

Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in dilated cardiomyopathy with heart failure.

Yihao Zhu · Xiaojing Yang · Yao Zu

Frontiers in cell and developmental biology · 2022 doi:10.3389/fcell.2022.1089915

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

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Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in dilated cardiomyopathy with heart failure.
doi
10.3389/fcell.2022.1089915
pmid
36544902
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Yihao Zhu
[1]
Xiaojing Yang
[2]
Yao Zu
journal
Frontiers in cell and developmental biology
year
2022
abstract
The etiologies and pathogenesis of dilated cardiomyopathy (DCM) with heart failure (HF) remain to be defined. Thus, exploring specific diagnosis biomarkers and mechanisms is urgently needed to improve this situation. In this study, three gene expression profiling datasets (GSE29819, GSE21610, GSE17800) and one single-cell RNA sequencing dataset (GSE95140) were obtained from the Gene Expression Omnibus (GEO) database. GSE29819 and GSE21610 were combined into the training group, while GSE17800 was the test group. We used the weighted gene co-expression network analysis (WGCNA) and identified fifteen driver genes highly associated with DCM with HF in the module. We performed the least absolute shrinkage and selection operator (LASSO) on the driver genes and then constructed five machine learning classifiers (random forest, gradient boosting machine, neural network, eXtreme gradient boosting, and support vector machine). Random forest was the best-performing classifier established on five Lasso-selected genes, which was utilized to select out NPPA, OMD, and PRELP for diagnosing DCM with HF. Moreover, we observed the up-regulation mRNA levels and robust diagnostic accuracies of NPPA, OMD, and PRELP in the training group and test group. Single-cell RNA-seq analysis further demonstrated their stable up-regulation expression patterns in various cardiomyocytes of DCM patients. Besides, through gene set enrichment analysis (GSEA), we found TGF-β signaling pathway, correlated with NPPA, OMD, and PRELP, was the underlying mechanism of DCM with HF. Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis.
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Wilcoxon test was performed to analyze the differential expression of key genes in DCM with HF group versus control group.
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Wilcoxon test was performed to analyze the differential expression of key genes in DCM with HF group versus control group.
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Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).
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Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).
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Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis.
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Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis.
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Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis.
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[184]
GSM2497141
[185]
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[186]
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[187]
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[188]
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[189]
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[190]
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[191]
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[192]
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[193]
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[194]
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[195]
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[196]
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[197]
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[198]
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[199]
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[200]
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[201]
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[202]
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[203]
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[204]
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[205]
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[206]
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[207]
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[208]
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[209]
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[210]
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[211]
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[212]
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[213]
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[214]
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[215]
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[216]
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[217]
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[218]
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[219]
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[220]
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[221]
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[222]
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[223]
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[224]
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[225]
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[226]
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[227]
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[228]
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[229]
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[230]
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[231]
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[232]
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[233]
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[234]
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[235]
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[236]
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[237]
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[238]
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[239]
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[240]
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[241]
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[242]
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[243]
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[244]
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[245]
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[246]
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[247]
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[248]
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[249]
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[250]
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[251]
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[252]
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[253]
GSM2497210
[254]
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[255]
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[256]
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[257]
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[258]
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[259]
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[260]
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[261]
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[262]
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[263]
GSM2497220
[264]
GSM2497221
[265]
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[266]
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[267]
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[268]
GSM2497225
[269]
GSM2497226
[270]
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[271]
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[272]
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[273]
GSM2497230
[274]
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[275]
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[276]
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[277]
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[278]
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[279]
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[280]
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[281]
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[282]
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[283]
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[284]
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[285]
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[286]
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[287]
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[288]
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[289]
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[290]
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[291]
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[292]
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[293]
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[294]
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[295]
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[296]
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[297]
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[298]
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[299]
GSM2497256
[300]
GSM2497257
[301]
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[302]
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[303]
GSM2497260
[304]
GSM2497261
[305]
GSM2497262
[306]
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[307]
GSM2497264
[308]
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[309]
GSM2497266
[310]
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[311]
GSM2497268
[312]
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[313]
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[314]
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[315]
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[316]
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[317]
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[318]
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[319]
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[320]
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[321]
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[322]
GSM2497279
[323]
GSM2497280
[324]
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[325]
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[326]
GSM2497283
[327]
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[328]
GSM2497285
[329]
GSM2497286
[330]
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[331]
GSM2497288
[332]
GSM2497289
[333]
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[334]
GSM2497291
[335]
GSM2497292
[336]
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[337]
GSM2497294
[338]
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[339]
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[340]
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[341]
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[342]
GSM2497299
[343]
GSM2497300
[344]
GSM2497301
[345]
GSM2497302
[346]
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[347]
GSM2497304
[348]
GSM2497305
[349]
GSM2497306
[350]
GSM2497307
[351]
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[352]
GSM2497309
[353]
GSM2497310
[354]
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[355]
GSM2497312
[356]
GSM2497313
[357]
GSM2497314
[358]
GSM2497315
[359]
GSM2497316
[360]
GSM2497317
[361]
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[362]
GSM2497319
[363]
GSM2497320
[364]
GSM2497321
[365]
GSM2497322
[366]
GSM2497323
[367]
GSM2497324
[368]
GSM2497325
[369]
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[370]
GSM2497327
[371]
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[372]
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[373]
GSM2497330
[374]
GSM2497331
[375]
GSM2497332
[376]
GSM2497333
[377]
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[378]
GSM2497335
[379]
GSM2497336
[380]
GSM2497337
[381]
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[382]
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[383]
GSM2497340
[384]
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[385]
GSM2497342
[386]
GSM2497343
[387]
GSM2497344
[388]
GSM2497345
[389]
GSM2497346
[390]
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[391]
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[392]
GSM2497349
[393]
GSM2497350
[394]
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[395]
GSM2497352
[396]
GSM2497353
[397]
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[398]
GSM2497355
[399]
GSM2497356
[400]
GSM2497357
[401]
GSM2497358
[402]
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[403]
GSM2497360
[404]
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[405]
GSM2497362
[406]
GSM2497363
[407]
GSM2497364
[408]
GSM2497365
[409]
GSM2497366
[410]
GSM2497367
[411]
GSM2497368
[412]
GSM2497369
[413]
GSM2497370
[414]
GSM2497371
[415]
GSM2497372
[416]
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[417]
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[418]
GSM2497375
[419]
GSM2497376
[420]
GSM2497377
[421]
GSM2497378
[422]
GSM2497379
[423]
GSM2497380
[424]
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[425]
GSM2497382
[426]
GSM2497383
[427]
GSM2497384
[428]
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[429]
GSM2497386
[430]
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[431]
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[432]
GSM2497389
[433]
GSM2497390
[434]
GSM2497391
[435]
GSM2497392
[436]
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[437]
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[438]
GSM2497395
[439]
GSM2497396
[440]
GSM2497397
[441]
GSM2497398
[442]
GSM2497399
[443]
GSM2497400
[444]
GSM2497401
[445]
GSM2497402
[446]
GSM2497403
[447]
GSM2497404
[448]
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[449]
GSM2497406
[450]
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[451]
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[452]
GSM2497409
[453]
GSM2497410
[454]
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[455]
GSM2497412
[456]
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[457]
GSM2497414
[458]
GSM2497415
[459]
GSM2497416
[460]
GSM2497417
[461]
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[462]
GSM2497419
[463]
GSM2497420
[464]
GSM2497421
[465]
GSM2497422
[466]
GSM2497423
[467]
GSM2497424
[468]
GSM2497425
[469]
GSM2497426
[470]
GSM2497427
[471]
GSM2497428
[472]
GSM2497429
[473]
GSM2497430
[474]
GSM2497431
[475]
GSM2497432
[476]
GSM2497433
[477]
GSM2497434
[478]
GSM2497435
[479]
GSM2497436
[480]
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[481]
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[482]
GSM2497439
[483]
GSM2497440
[484]
GSM2497441
[485]
GSM2497442
[486]
GSM2497443
[487]
GSM2497444
[488]
GSM2497445
[489]
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[490]
GSM2497447
[491]
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[492]
GSM2497449
[493]
GSM2497450
[494]
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[495]
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[496]
GSM2497453
[497]
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[498]
GSM2497455
[499]
GSM2497456
[500]
GSM2497457
[501]
GSM2497458
[502]
GSM2497459
[503]
GSM2497460
[504]
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[505]
GSM2497462
[506]
GSM2497463
[507]
GSM2497464
[508]
GSM2497465
[509]
GSM2497466
[510]
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[511]
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[512]
GSM2497469
[513]
GSM2497470
[514]
GSM2497471
[515]
GSM2497472
[516]
GSM2497473
[517]
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[518]
GSM2497475
[519]
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[520]
GSM2497477
[521]
GSM2497478
[522]
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[523]
GSM2497480
[524]
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[525]
GSM2497482
[526]
GSM2497483
[527]
GSM2497484
[528]
GSM2497485
[529]
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[530]
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[531]
GSM2497488
[532]
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[533]
GSM2497490
[534]
GSM2497491
[535]
GSM2497492
[536]
GSM2497493
[537]
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[538]
GSM2497495
[539]
GSM2497496
[540]
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[541]
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[542]
GSM2497499
[543]
GSM2497500
[544]
GSM2497501
[545]
GSM2497502
[546]
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[547]
GSM2497504
[548]
GSM2497505
[549]
GSM2497506
[550]
GSM2497507
[551]
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[552]
GSM2497509
[553]
GSM2497510
[554]
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[555]
GSM2497512
[556]
GSM2497513
[557]
GSM2497514
[558]
GSM2497515
[559]
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[560]
GSM2497517
[561]
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[562]
GSM2497519
[563]
GSM2497520
[564]
GSM2497521
[565]
GSM2497522
[566]
GSM2497523
[567]
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[568]
GSM2497525
[569]
GSM2497526
[570]
GSM2497527
[571]
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[572]
GSM2497529
[573]
GSM2497530
[574]
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[575]
GSM2497532
[576]
GSM2497533
[577]
GSM2497534
[578]
GSM2497535
[579]
GSM2497536
[580]
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[581]
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[582]
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[583]
GSM2497540
[584]
GSM2497541
[585]
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[586]
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[587]
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[588]
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[589]
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[590]
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[591]
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[592]
GSM2497549
[593]
GSM2497550
[594]
GSM2497551
[595]
GSM2497552
[596]
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[597]
GSM2497554
[598]
GSM2497555
[599]
GSM2497556
[600]
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[601]
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[602]
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[603]
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[604]
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[605]
GSM2497562
[606]
GSM2497563
[607]
GSM2497564
[608]
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[609]
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[610]
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[611]
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[612]
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[613]
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[614]
GSM2497571
[615]
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[616]
GSM2497573
[617]
GSM2497574
[618]
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[619]
GSM2497576
[620]
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[621]
GSM2497578
[622]
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[623]
GSM2497580
[624]
GSM2497581
[625]
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[626]
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[627]
GSM2497584
[628]
GSM2497585
[629]
GSM2497586
[630]
GSM2497587
[631]
GSM3081177
[632]
GSM3081178
[633]
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[634]
GSM3081180
[635]
GSM3081181
[636]
GSM3081182
[637]
GSM3081183
[638]
GSM3081184
[639]
GSM3081185
[640]
GSM3081186
[641]
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[642]
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[643]
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[644]
GSM3081190
[645]
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[646]
GSM3081192
[647]
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[648]
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[649]
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[650]
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[651]
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[652]
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[653]
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[654]
GSM3081200
[655]
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[656]
GSM3081202
[657]
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[658]
GSM3081204
[659]
GSM3081205
[660]
GSM3081206
[661]
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[662]
GSM3081208
[663]
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[664]
GSM3081210
[665]
GSM3081211
[666]
GSM3081212
[667]
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[668]
GSM3081214
[669]
GSM3081215
[670]
GSM3081216
[671]
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[672]
GSM3081218
[673]
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[674]
GSM3081220
[675]
GSM3081221
[676]
GSM3081222
[677]
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[678]
GSM3081224
[679]
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[680]
GSM3081226
[681]
GSM3081227
[682]
GSM3081228
[683]
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[684]
GSM3081230
[685]
GSM3081231
[686]
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[687]
GSM3081233
[688]
GSM3081234
[689]
GSM3081235
[690]
GSM3081236
[691]
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[692]
GSM3081238
[693]
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[694]
GSM3081240
[695]
GSM3081241
[696]
GSM3081242
[697]
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[698]
GSM3081244
[699]
GSM3081245
[700]
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[701]
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[702]
GSM3081248
[703]
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[704]
GSM3081250
[705]
GSM3081251
[706]
GSM3081252
[707]
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[708]
GSM3081254
[709]
GSM3081255
[710]
GSM3081256
[711]
GSM3081257
[712]
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[713]
GSM3081259
[714]
GSM3081260
[715]
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[716]
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[717]
GSM3081263
[718]
GSM3081264
[719]
GSM3081265
[720]
GSM3081266
[721]
GSM3081267
[722]
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[723]
GSM3081269
[724]
GSM3081270
[725]
GSM3081271
[726]
GSM3081272
[727]
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[728]
GSM3081274
[729]
GSM3081275
[730]
GSM3081276
[731]
GSM3081277
[732]
GSM3081278
[733]
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[734]
GSM3081280
[735]
GSM3081281
[736]
GSM3081282
[737]
GSM3081283
[738]
GSM3081284
[739]
GSM3081285
[740]
GSM3081286
[741]
GSM3081287
[742]
GSM3081288
[743]
GSM3081289
[744]
GSM3081290
[745]
GSM3081291
[746]
GSM3081292
[747]
GSM3081293
[748]
GSM3081294
[749]
GSM3081295
[750]
GSM3081296
[751]
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[752]
GSM3081298
[753]
GSM3081299
[754]
GSM3081300
[755]
GSM3081301
[756]
GSM3081302
[757]
GSM3081303
[758]
GSM3081304
[759]
GSM3081305
[760]
GSM3081306
[761]
GSM3081307
[762]
GSM3081308
[763]
GSM3081309
[764]
GSM3081310
[765]
GSM3081311
[766]
GSM3081312
[767]
GSM3081313
[768]
GSM3081314
[769]
GSM3081315
[770]
GSM3081316
[771]
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[772]
GSM3081318
[773]
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[774]
GSM3081320
[775]
GSM3081321
[776]
GSM3081322
[777]
GSM3081323
[778]
GSM3081324
[779]
GSM3081325
[780]
GSM3081326
[781]
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[782]
GSM3081328
[783]
GSM3081329
[784]
GSM3081330
[785]
GSM3081331
[786]
GSM3081332
[787]
GSM3081333
[788]
GSM3081334
[789]
GSM3081335
[790]
GSM3081336
[791]
GSM3081337
[792]
GSM3081338
[793]
GSM3081339
[794]
GSM3081340
[795]
GSM3081341
[796]
GSM3081342
[797]
GSM3081343
[798]
GSM3081344
[799]
GSM3081345
[800]
GSM3081346
[801]
GSM3081347
[802]
GSM3081348
[803]
GSM3081349
[804]
GSM3081350
[805]
GSM3081351
[806]
GSM3081352
[807]
GSM3081353
[808]
GSM3081354
[809]
GSM3081355
[810]
GSM3081356
[811]
GSM3081357
[812]
GSM3081358
[813]
GSM3081359
[814]
GSM3081360
[815]
GSM3081361
[816]
GSM3081362
[817]
GSM3081363
[818]
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[819]
GSM3081365
[820]
GSM3081366
[821]
GSM3081367
[822]
GSM3081368
[823]
GSM3081369
[824]
GSM3081370
[825]
GSM3081371
[826]
GSM3081372
[827]
GSM3081373
[828]
GSM3081374
[829]
GSM3081375
[830]
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[831]
GSM3081377
[832]
GSM3081378
[833]
GSM3081379
[834]
GSM3081380
[835]
GSM3081381
[836]
GSM3081382
[837]
GSM3081383
[838]
GSM3081384
[839]
GSM3081385
[840]
GSM3081386
[841]
GSM3081387
[842]
GSM3081388
[843]
GSM3081389
[844]
GSM3081390
[845]
GSM3081391
[846]
GSM3081392
[847]
GSM3081393
[848]
GSM3081394
[849]
GSM3081395
[850]
GSM3081396
[851]
GSM3081397
[852]
GSM3081398
[853]
GSM3081399
[854]
GSM3081400
[855]
GSM3081401
[856]
GSM3081402
[857]
GSM3081403
[858]
GSM3081404
[859]
GSM3081405
[860]
GSM3081406
[861]
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sample_count
1190
group_sizes
null
group_sizes_basis
null
platform
17021;16791
taxon
Homo sapiens; Mus musculus
title
Cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure (RNA-Seq)
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 8 items
[0]
asset:data:geo:GSE17800 not downloaded
[1]
asset:data:geo:GSE17800 licence not read
[2]
asset:data:geo:GSE21610 not downloaded
[3]
asset:data:geo:GSE21610 licence not read
[4]
asset:data:geo:GSE29819 not downloaded
[5]
asset:data:geo:GSE29819 licence not read
[6]
asset:data:geo:GSE95140 not downloaded
[7]
asset:data:geo:GSE95140 licence not read
analysis object · 4 fields
state
partial
methods array · 4 items
[0] object · 10 fields
id
method-1
family
group_comparison
specific
wilcoxon
label
Group comparison
dsl_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
two_or_more_groups_continuous
evidence object · 3 fields
score
1
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verbatim
quote
Wilcoxon test was performed to analyze the differential expression of key genes in DCM with HF group versus control group.
[1] object · 10 fields
id
method-2
family
machine_learning
specific
random_forest
label
Machine learning
dsl_operations array · 0 items
missing_operations array · 1 item
[0]
machine_learning_random_forest
expressible
false
parameters object · 0 fields
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.7
band
medium
quote
random forest
[2] object · 10 fields
id
method-3
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machine_learning
specific
support_vector_machine
label
Machine learning
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[0]
train_classifier
[1]
cross_validate
[2]
roc_auc
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.7
band
medium
quote
support vector machine
[3] object · 10 fields
id
method-4
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machine_learning
specific
gradient_boosting
label
Machine learning
dsl_operations array · 3 items
[0]
train_classifier
[1]
cross_validate
[2]
roc_auc
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.7
band
medium
quote
gradient boosting
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gaps array · 1 item
[0]
method.group_comparison_wilcoxon
capability object · 3 fields
state
complete
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[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
false
required_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 4 items
[0]
GSE29819
[1]
GSE21610
[2]
GSE17800
[3]
GSE95140
resolved_accessions array · 4 items
[0]
GSE29819
[1]
GSE21610
[2]
GSE17800
[3]
GSE95140
statements array · 1 item
[0]
Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).
basis
The paper names GSE29819, GSE21610, GSE17800, GSE95140 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
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assets array · 2 items
[0]
source:pmid:36544902
[1]
data:geo:GSE17800
steps array · 0 items
must_build object · 5 fields
dsl_operations array · 1 item
[0] object · 3 fields
operation
group_comparison_wilcoxon
priority
null
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readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE17800
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-11-01T18:20:32Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
18497
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2052
cached_tokens
128
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[0] object · 4 fields
id
extraction
state
complete
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MiniMax-M3.1-Flash
provider
minimax
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[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
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absent
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not_run
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null
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[0]
execution.not_run
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[0] object · 3 fields
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pmid:36544902
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paper
label
pmid:36544902
[1] object · 3 fields
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source:pmid:36544902
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manuscript
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PMID 36544902 full text
[2] object · 3 fields
id
data:geo:GSE17800
type
dataset
label
GEO GSE17800
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
used array · 3 items
[0] object · 3 fields
id
pmid:36544902
type
paper
label
pmid:36544902
[1] object · 3 fields
id
source:pmid:36544902
type
manuscript
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PMID 36544902 full text
[2] object · 3 fields
id
data:geo:GSE17800
type
dataset
label
GEO GSE17800
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-36544902
type
extraction
used array · 1 item
[0]
source:pmid:36544902
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agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE17800
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE17800
agent
agent:corpus-assay-engine
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[0] object · 3 fields
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agent:corpus-assay-engine
type
software
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Corpus assay engine
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agent:minimax-reader
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software
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MiniMax literature reader
source_run_id
reading-sci-2026-11-01
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
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snapshot_id
ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:36544902
parent_hash
sha256:803bd3440ecd96f2f663067e05c9ebd035f6923113e853f33d94d102e8ab8db4
fork_of
null
gaps array · 14 items
[0]
asset:data:geo:GSE17800 licence not read
[1]
asset:data:geo:GSE17800 not downloaded
[2]
asset:data:geo:GSE21610 licence not read
[3]
asset:data:geo:GSE21610 not downloaded
[4]
asset:data:geo:GSE29819 licence not read
[5]
asset:data:geo:GSE29819 not downloaded
[6]
asset:data:geo:GSE95140 licence not read
[7]
asset:data:geo:GSE95140 not downloaded
[8]
execution.not_run
[9]
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[10]
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[11]
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[12]
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[13]
step:run_analysis blocked on method:group_comparison_wilcoxon
assays array · 3 items
[0] object · 11 fields
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data_generation
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scrna_seq
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99e1195c7d6f
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support_state
unsupported
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assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 4 items
[0]
asets (GSE29819, GSE21610, GSE17800) and one single-cell RNA sequencing dataset (GSE95140) were obtained from the Ge
[1]
PRELP in the training group and test group. Single-cell RNA-seq analysis further demonstrated their stable u
[2]
05 was considered statistically significant. Single-cell RNA-seq analysis revealed the over-expression patter
[3]
OMD, and PRELP in DCM patients, we conducted single-cell RNA-seq analysis on GSE95140. The quality control, d
order_basis
paper_text_order:396
id
assay:1
[1] object · 11 fields
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data_generation
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rna_seq
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99e1195c7d6f
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partial
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assay_lexicon
99e1195c7d6f
confidence
0.99
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[0]
e training group and test group. Single-cell RNA-seq analysis further demonstrated their stable u
[1]
dered statistically significant. Single-cell RNA-seq analysis revealed the over-expression patter
[2]
LP in DCM patients, we conducted single-cell RNA-seq analysis on GSE95140. The quality control, d
[3]
key genes expression pattern on single-cell RNA-seq analysis. (A) UMAP projection of distinct no
order_basis
paper_text_order:408
id
assay:2
[2] object · 11 fields
role
analysis
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group_comparison
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f2132e96ae6c7a4e
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partial
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dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
Wilcoxon test was performed to analyze the differential expression of key genes in DCM with HF group versus control group.
order_basis
consumes_earlier_output
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assay:3
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36544902", "kind": "science-record", "revision": 3, "content_hash": "sha256:7ab24ff4c68b7080ba8716f6a486463be4f41a4d1f6b792d38b398f9f4451234", "created_at": "2026-11-01T19:01:04Z", "updated_at": "2026-11-01T22:08:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in dilated cardiomyopathy with heart failure.", "doi": "10.3389/fcell.2022.1089915", "pmid": "36544902", "authors": ["Yihao Zhu", "Xiaojing Yang", "Yao Zu"], "journal": "Frontiers in cell and developmental biology", "year": 2022, "abstract": "The etiologies and pathogenesis of dilated cardiomyopathy (DCM) with heart failure (HF) remain to be defined. Thus, exploring specific diagnosis biomarkers and mechanisms is urgently needed to improve this situation. In this study, three gene expression profiling datasets (GSE29819, GSE21610, GSE17800) and one single-cell RNA sequencing dataset (GSE95140) were obtained from the Gene Expression Omnibus (GEO) database. GSE29819 and GSE21610 were combined into the training group, while GSE17800 was the test group. We used the weighted gene co-expression network analysis (WGCNA) and identified fifteen driver genes highly associated with DCM with HF in the module. We performed the least absolute shrinkage and selection operator (LASSO) on the driver genes and then constructed five machine learning classifiers (random forest, gradient boosting machine, neural network, eXtreme gradient boosting, and support vector machine). Random forest was the best-performing classifier established on five Lasso-selected genes, which was utilized to select out NPPA, OMD, and PRELP for diagnosing DCM with HF. Moreover, we observed the up-regulation mRNA levels and robust diagnostic accuracies of NPPA, OMD, and PRELP in the training group and test group. Single-cell RNA-seq analysis further demonstrated their stable up-regulation expression patterns in various cardiomyocytes of DCM patients. Besides, through gene set enrichment analysis (GSEA), we found TGF-β signaling pathway, correlated with NPPA, OMD, and PRELP, was the underlying mechanism of DCM with HF. Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis.", "claims": [{"id": "claim-method", "statement": "Wilcoxon test was performed to analyze the differential expression of key genes in DCM with HF group versus control group.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36544902", "locator": "sections[12] \"Statistical analysis\" paragraph 2", "quote": "Wilcoxon test was performed to analyze the differential expression of key genes in DCM with HF group versus control group."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36544902", "locator": "sections[24] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36544902", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36544902"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE17800"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE17800"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36544902", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fcell.2022.1089915", "sha256": "sha256:bbc4c347b1315793a6d76a4a905028afc13e9b6c2b91036d4f3614cf73070a15", "bytes": 65589, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fcell.2022.1089915", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9760806", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE17800", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17800", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE17800", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM444224", "GSM444226", "GSM444228", "GSM444230", "GSM444232", "GSM444234", "GSM444236", "GSM444238", "GSM444240", "GSM444242", "GSM444244", "GSM444246", "GSM444248", "GSM444250", "GSM444252", "GSM444254", "GSM444256", "GSM444258", "GSM444260", "GSM444262", "GSM444264", "GSM444266", "GSM444268", "GSM444270", "GSM444272", "GSM444274", "GSM444276", "GSM444278", "GSM444280", "GSM444282", "GSM444284", "GSM444286", "GSM444288", "GSM444289", "GSM444290", "GSM444291", "GSM444292", "GSM444293", "GSM444294", "GSM444295", "GSM444296", "GSM444297", "GSM444298", "GSM444299", "GSM444300", "GSM444301", "GSM444302", "GSM444303"], "sample_count": 48, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Myocardial gene expression profiles and cardiodepressant autoantibodies predict response of patients with dilated cardiomyopathy to immunoadsorption therapy", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE21610", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21610", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE21610", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM545657", "GSM545658", "GSM545659", "GSM545660", "GSM545661", "GSM545662", "GSM545663", "GSM545664", "GSM545665", "GSM545666", "GSM545667", "GSM545668", "GSM545669", "GSM545670", "GSM545671", "GSM545672", "GSM545673", "GSM545674", "GSM545675", "GSM545676", "GSM545677", "GSM545678", "GSM545679", "GSM545680", "GSM545681", "GSM545682", "GSM545683", "GSM545684", "GSM545685", "GSM545686", "GSM545687", "GSM545688", "GSM545689", "GSM545690", "GSM545691", "GSM545692", "GSM545693", "GSM545694", "GSM545695", "GSM545696", "GSM545697", "GSM545698", "GSM545699", "GSM545700", "GSM545701", "GSM545702", "GSM545703", "GSM545704", "GSM545705", "GSM545706", "GSM545707", "GSM545708", "GSM545709", "GSM545710", "GSM545711", "GSM545712", "GSM545713", "GSM545714", "GSM545715", "GSM545716", "GSM545717", "GSM545718", "GSM545719", "GSM545720", "GSM545721", "GSM545722", "GSM545723", "GSM545724"], "sample_count": 68, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gene expression analysis in non-failing and failing myocardium pre and post pulsatile and non-pulsatile VAD support", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE29819", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE29819", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE29819", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM738990", "GSM738991", "GSM738992", "GSM738993", "GSM738994", "GSM738995", "GSM738996", "GSM738997", "GSM738998", "GSM738999", "GSM739000", "GSM739001", "GSM739002", "GSM739003", "GSM739004", "GSM739005", "GSM739006", "GSM739007", "GSM739008", "GSM739009", "GSM739010", "GSM739011", "GSM739012", "GSM739013", "GSM739014", "GSM739015", "GSM739016", "GSM739017", "GSM739018", "GSM739019", "GSM739020", "GSM739021", "GSM739022", "GSM739023", "GSM739024", "GSM739025", "GSM739026", "GSM739027"], "sample_count": 38, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Myocardial transcriptome analysis of human arrhythmogenic right ventricular cardiomyopathy (ARVC)", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE95140", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE95140", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE95140", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2496957", "GSM2496958", "GSM2496959", "GSM2496960", "GSM2496961", "GSM2496962", "GSM2496963", "GSM2496964", "GSM2496965", "GSM2496966", "GSM2496967", "GSM2496968", "GSM2496969", "GSM2496970", "GSM2496971", "GSM2496972", "GSM2496973", "GSM2496974", "GSM2496975", "GSM2496976", "GSM2496977", "GSM2496978", "GSM2496979", "GSM2496980", "GSM2496981", "GSM2496982", "GSM2496983", "GSM2496984", "GSM2496985", "GSM2496986", "GSM2496987", "GSM2496988", "GSM2496989", "GSM2496990", "GSM2496991", "GSM2496992", "GSM2496993", "GSM2496994", "GSM2496995", "GSM2496996", "GSM2496997", "GSM2496998", "GSM2496999", "GSM2497000", "GSM2497001", "GSM2497002", "GSM2497003", 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"GSM3081729", "GSM3081730", "GSM3081731", "GSM3081732", "GSM3081733", "GSM3081734", "GSM3081735"], "sample_count": 1190, "group_sizes": null, "group_sizes_basis": null, "platform": "17021;16791", "taxon": "Homo sapiens; Mus musculus", "title": "Cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure (RNA-Seq)", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE17800 not downloaded", "asset:data:geo:GSE17800 licence not read", "asset:data:geo:GSE21610 not downloaded", "asset:data:geo:GSE21610 licence not read", "asset:data:geo:GSE29819 not downloaded", "asset:data:geo:GSE29819 licence not read", "asset:data:geo:GSE95140 not downloaded", "asset:data:geo:GSE95140 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Wilcoxon test was performed to analyze the differential expression of key genes in DCM with HF group versus control group."}}, {"id": "method-2", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "random forest"}}, {"id": "method-3", "family": "machine_learning", "specific": "support_vector_machine", "label": "Machine learning", "dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "support vector machine"}}, {"id": "method-4", "family": "machine_learning", "specific": "gradient_boosting", "label": "Machine learning", "dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "gradient boosting"}}], "targets": [], "gaps": ["method.group_comparison_wilcoxon"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": false, "required_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE29819", "GSE21610", "GSE17800", "GSE95140"], "resolved_accessions": ["GSE29819", "GSE21610", "GSE17800", "GSE95140"], "statements": ["Publicly available datasets were analyzed in this study. This data can be found here: Three gene expression profiling datasets of DCM with HF (GSE29819, GSE21610, GSE17800) and one single-cell RNA-sequencing dataset of DCM (GSE95140) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/)."], "basis": "The paper names GSE29819, GSE21610, GSE17800, GSE95140 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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Single-cell RNA-seq analysis further demonstrated their stable u", "05 was considered statistically significant. Single-cell RNA-seq analysis revealed the over-expression patter", "OMD, and PRELP in DCM patients, we conducted single-cell RNA-seq analysis on GSE95140. The quality control, d"], "order_basis": "paper_text_order:396", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["e training group and test group. Single-cell RNA-seq analysis further demonstrated their stable u", "dered statistically significant. Single-cell RNA-seq analysis revealed the over-expression patter", "LP in DCM patients, we conducted single-cell RNA-seq analysis on GSE95140. The quality control, d", "key genes expression pattern on single-cell RNA-seq analysis. (A) UMAP projection of distinct no"], "order_basis": "paper_text_order:408", "id": "assay:2"}, {"role": "analysis", "definition_id": "group_comparison", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Wilcoxon test was performed to analyze the differential expression of key genes in DCM with HF group versus control group."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}