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pmid:33999966

Comparison of machine-learning methodologies for accurate diagnosis of sepsis using microarray gene expression data.

Dominik Schaack · Markus A Weigand · Florian Uhle

PloS one · 2021 doi:10.1371/journal.pone.0251800

Paper

complete

Experiment

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Data

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Analysis

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Comparison of machine-learning methodologies for accurate diagnosis of sepsis using microarray gene expression data.
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10.1371/journal.pone.0251800
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Dominik Schaack
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Markus A Weigand
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Florian Uhle
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PloS one
year
2021
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We investigate the feasibility of molecular-level sample classification of sepsis using microarray gene expression data merged by in silico meta-analysis. Publicly available data series were extracted from NCBI Gene Expression Omnibus and EMBL-EBI ArrayExpress to create a comprehensive meta-analysis microarray expression set (meta-expression set). Measurements had to be obtained via microarray-technique from whole blood samples of adult or pediatric patients with sepsis diagnosed based on international consensus definition immediately after admission to the intensive care unit. We aggregate trauma patients, systemic inflammatory response syndrome (SIRS) patients, and healthy controls in a non-septic entity. Differential expression (DE) analysis is compared with machine-learning-based solutions like decision tree (DT), random forest (RF), support vector machine (SVM), and deep-learning neural networks (DNNs). We evaluated classifier training and discrimination performance in 100 independent iterations. To test diagnostic resilience, we gradually degraded expression data in multiple levels. Clustering of expression values based on DE genes results in partial identification of sepsis samples. In contrast, RF, SVM, and DNN provide excellent diagnostic performance measured in terms of accuracy and area under the curve (>0.96 and >0.99, respectively). We prove DNNs as the most resilient methodology, virtually unaffected by targeted removal of DE genes. By surpassing most other published solutions, the presented approach substantially augments current diagnostic capability in intensive care medicine.
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With the iterative repetition of the entire approach, Stratified ShuffleSplit cross-validation is implemented to prove the reproducibility of classification results.
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[78]
GSM901391
[79]
GSM901392
[80]
GSM901393
[81]
GSM901394
[82]
GSM901395
[83]
GSM901396
[84]
GSM901397
[85]
GSM901398
[86]
GSM901399
[87]
GSM901400
[88]
GSM901401
[89]
GSM901402
[90]
GSM901403
[91]
GSM901404
[92]
GSM901405
[93]
GSM901406
[94]
GSM901407
[95]
GSM901408
[96]
GSM901409
[97]
GSM901410
[98]
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[99]
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[100]
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[101]
GSM901414
[102]
GSM901415
[103]
GSM901416
[104]
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[105]
GSM901418
[106]
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[107]
GSM901420
[108]
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[109]
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[110]
GSM901423
[111]
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[112]
GSM901425
[113]
GSM901426
[114]
GSM901427
[115]
GSM901428
[116]
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[117]
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[118]
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[119]
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[120]
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[121]
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[122]
GSM901435
[123]
GSM901436
[124]
GSM901437
[125]
GSM901438
[126]
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[127]
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[128]
GSM901441
[129]
GSM901442
[130]
GSM901443
[131]
GSM901444
[132]
GSM901445
[133]
GSM901446
[134]
GSM901447
[135]
GSM901448
[136]
GSM901449
[137]
GSM901450
[138]
GSM901451
[139]
GSM901452
[140]
GSM901453
[141]
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[142]
GSM901455
[143]
GSM901456
[144]
GSM901457
[145]
GSM901458
[146]
GSM901459
[147]
GSM901460
[148]
GSM901461
[149]
GSM901462
[150]
GSM901463
[151]
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[152]
GSM901465
[153]
GSM901466
[154]
GSM901467
[155]
GSM901468
[156]
GSM901469
[157]
GSM901470
[158]
GSM901471
[159]
GSM901472
[160]
GSM901473
[161]
GSM901474
[162]
GSM901475
[163]
GSM901476
[164]
GSM901477
[165]
GSM901478
[166]
GSM901479
[167]
GSM901480
[168]
GSM901481
[169]
GSM901482
[170]
GSM901483
[171]
GSM901484
[172]
GSM901485
[173]
GSM901486
[174]
GSM901487
[175]
GSM901488
[176]
GSM901489
[177]
GSM901490
[178]
GSM901491
[179]
GSM901492
[180]
GSM901493
[181]
GSM901494
[182]
GSM901495
[183]
GSM901496
[184]
GSM901497
[185]
GSM901498
[186]
GSM901499
[187]
GSM901500
[188]
GSM901501
[189]
GSM901502
[190]
GSM901503
[191]
GSM901504
[192]
GSM901505
[193]
GSM901506
[194]
GSM901507
[195]
GSM901508
[196]
GSM901509
[197]
GSM901510
[198]
GSM901511
[199]
GSM901512
[200]
GSM901513
[201]
GSM901514
[202]
GSM901515
[203]
GSM901516
[204]
GSM901517
[205]
GSM901518
[206]
GSM901519
[207]
GSM901520
[208]
GSM901521
[209]
GSM901522
[210]
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[211]
GSM901524
[212]
GSM901525
[213]
GSM901526
[214]
GSM901527
[215]
GSM901528
[216]
GSM901529
[217]
GSM901530
[218]
GSM901531
[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]
GSM901537
[225]
GSM901538
[226]
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[227]
GSM901540
[228]
GSM901541
[229]
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[230]
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[231]
GSM901544
[232]
GSM901545
[233]
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[234]
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[235]
GSM901548
[236]
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[237]
GSM901550
[238]
GSM901551
[239]
GSM901552
[240]
GSM901553
[241]
GSM901554
[242]
GSM901555
[243]
GSM901556
[244]
GSM901557
[245]
GSM901558
[246]
GSM901559
[247]
GSM901560
[248]
GSM901561
[249]
GSM901562
[250]
GSM901563
[251]
GSM901564
[252]
GSM901565
[253]
GSM901566
[254]
GSM901567
[255]
GSM901568
[256]
GSM901569
[257]
GSM901570
[258]
GSM901571
[259]
GSM901572
[260]
GSM901573
[261]
GSM901574
[262]
GSM901575
[263]
GSM901576
[264]
GSM901577
[265]
GSM901578
[266]
GSM901579
[267]
GSM901580
[268]
GSM901581
[269]
GSM901582
[270]
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[271]
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[272]
GSM901585
[273]
GSM901586
[274]
GSM901587
[275]
GSM901588
[276]
GSM901589
[277]
GSM901590
[278]
GSM901591
[279]
GSM901592
[280]
GSM901593
[281]
GSM901594
[282]
GSM901595
[283]
GSM901596
[284]
GSM901597
[285]
GSM901598
[286]
GSM901599
[287]
GSM901600
[288]
GSM901601
[289]
GSM901602
[290]
GSM901603
[291]
GSM901604
[292]
GSM901605
[293]
GSM901606
[294]
GSM901607
[295]
GSM901608
[296]
GSM901609
[297]
GSM901610
[298]
GSM901611
[299]
GSM901612
[300]
GSM901613
[301]
GSM901614
[302]
GSM901615
[303]
GSM901616
[304]
GSM901617
[305]
GSM901618
[306]
GSM901619
[307]
GSM901620
[308]
GSM901621
[309]
GSM901622
[310]
GSM901623
[311]
GSM901624
[312]
GSM901625
[313]
GSM901626
[314]
GSM901627
[315]
GSM901628
[316]
GSM901629
[317]
GSM901630
[318]
GSM901631
[319]
GSM901632
[320]
GSM901633
[321]
GSM901634
[322]
GSM901635
[323]
GSM901636
[324]
GSM901637
[325]
GSM901638
[326]
GSM901639
[327]
GSM901640
[328]
GSM901641
[329]
GSM901642
[330]
GSM901643
[331]
GSM901644
[332]
GSM901645
[333]
GSM901646
[334]
GSM901647
[335]
GSM901648
[336]
GSM901649
[337]
GSM901650
[338]
GSM901651
[339]
GSM901652
[340]
GSM901653
[341]
GSM901654
[342]
GSM901655
[343]
GSM901656
[344]
GSM901657
[345]
GSM901658
[346]
GSM901659
[347]
GSM901660
[348]
GSM901661
[349]
GSM901662
[350]
GSM901663
[351]
GSM901664
[352]
GSM901665
[353]
GSM901666
[354]
GSM901667
[355]
GSM901668
[356]
GSM901669
[357]
GSM901670
[358]
GSM901671
[359]
GSM901672
[360]
GSM901673
[361]
GSM901674
[362]
GSM901675
[363]
GSM901676
[364]
GSM901677
[365]
GSM901678
[366]
GSM901679
[367]
GSM901680
[368]
GSM901681
[369]
GSM901682
[370]
GSM901683
[371]
GSM901684
[372]
GSM901685
[373]
GSM901686
[374]
GSM901687
[375]
GSM901688
[376]
GSM901689
[377]
GSM901690
[378]
GSM901691
[379]
GSM901692
[380]
GSM901693
[381]
GSM901694
[382]
GSM901695
[383]
GSM901696
[384]
GSM901697
[385]
GSM901698
[386]
GSM901699
[387]
GSM901700
[388]
GSM901701
[389]
GSM901702
[390]
GSM901703
[391]
GSM901704
[392]
GSM901705
[393]
GSM901706
[394]
GSM901707
[395]
GSM901708
[396]
GSM901709
[397]
GSM901710
[398]
GSM901711
[399]
GSM901712
[400]
GSM901713
[401]
GSM901714
[402]
GSM901715
[403]
GSM901716
[404]
GSM901717
[405]
GSM901718
[406]
GSM901719
[407]
GSM901720
[408]
GSM901721
[409]
GSM901722
[410]
GSM901723
[411]
GSM901724
[412]
GSM901725
[413]
GSM901726
[414]
GSM901727
[415]
GSM901728
[416]
GSM901729
[417]
GSM901730
[418]
GSM901731
[419]
GSM901732
[420]
GSM901733
[421]
GSM901734
[422]
GSM901735
[423]
GSM901736
[424]
GSM901737
[425]
GSM901738
[426]
GSM901739
[427]
GSM901740
[428]
GSM901741
[429]
GSM901742
[430]
GSM901743
[431]
GSM901744
[432]
GSM901745
[433]
GSM901746
[434]
GSM901747
[435]
GSM901748
[436]
GSM901749
[437]
GSM901750
[438]
GSM901751
[439]
GSM901752
[440]
GSM901753
[441]
GSM901754
[442]
GSM901755
[443]
GSM901756
[444]
GSM901757
[445]
GSM901758
[446]
GSM901759
[447]
GSM901760
[448]
GSM901761
[449]
GSM901762
[450]
GSM901763
[451]
GSM901764
[452]
GSM901765
[453]
GSM901766
[454]
GSM901767
[455]
GSM901768
[456]
GSM901769
[457]
GSM901770
[458]
GSM901771
[459]
GSM901772
[460]
GSM901773
[461]
GSM901774
[462]
GSM901775
[463]
GSM901776
[464]
GSM901777
[465]
GSM901778
[466]
GSM901779
[467]
GSM901780
[468]
GSM901781
[469]
GSM901782
[470]
GSM901783
[471]
GSM901784
[472]
GSM901785
[473]
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[474]
GSM901787
[475]
GSM901788
[476]
GSM901789
[477]
GSM901790
[478]
GSM901791
[479]
GSM901792
[480]
GSM901793
[481]
GSM901794
[482]
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[483]
GSM901796
[484]
GSM901797
[485]
GSM901798
[486]
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[487]
GSM901800
[488]
GSM901801
[489]
GSM901802
[490]
GSM901803
[491]
GSM901804
[492]
GSM901805
[493]
GSM901806
[494]
GSM901807
[495]
GSM901808
[496]
GSM901809
[497]
GSM901810
[498]
GSM901811
[499]
GSM901812
[500]
GSM901813
[501]
GSM901814
[502]
GSM901815
[503]
GSM901816
[504]
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[505]
GSM901818
[506]
GSM901819
[507]
GSM901820
[508]
GSM901821
[509]
GSM901822
[510]
GSM901823
[511]
GSM901824
[512]
GSM901825
[513]
GSM901826
[514]
GSM901827
[515]
GSM901828
[516]
GSM901829
[517]
GSM901830
[518]
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[519]
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[520]
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[521]
GSM901834
[522]
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[523]
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[524]
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[525]
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[526]
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[527]
GSM901840
[528]
GSM901841
[529]
GSM901842
[530]
GSM901843
[531]
GSM901844
[532]
GSM901845
[533]
GSM901846
[534]
GSM901847
[535]
GSM901848
[536]
GSM901849
[537]
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[538]
GSM901851
[539]
GSM901852
[540]
GSM901853
[541]
GSM901854
[542]
GSM901855
[543]
GSM901856
[544]
GSM901857
[545]
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[546]
GSM901859
[547]
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[548]
GSM901861
[549]
GSM901862
[550]
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[551]
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[552]
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[553]
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[554]
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[555]
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[556]
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[557]
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[558]
GSM901871
[559]
GSM901872
[560]
GSM901873
[561]
GSM901874
[562]
GSM901875
[563]
GSM901876
[564]
GSM901877
[565]
GSM901878
[566]
GSM901879
[567]
GSM901880
[568]
GSM901881
[569]
GSM901882
[570]
GSM901883
[571]
GSM901884
[572]
GSM901885
[573]
GSM901886
[574]
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[575]
GSM901888
[576]
GSM901889
[577]
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[578]
GSM901891
[579]
GSM901892
[580]
GSM901893
[581]
GSM901894
[582]
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[583]
GSM901896
[584]
GSM901897
[585]
GSM901898
[586]
GSM901899
[587]
GSM901900
[588]
GSM901901
[589]
GSM901902
[590]
GSM901903
[591]
GSM901904
[592]
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[593]
GSM901906
[594]
GSM901907
[595]
GSM901908
[596]
GSM901909
[597]
GSM901910
[598]
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[599]
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[600]
GSM901913
[601]
GSM901914
[602]
GSM901915
[603]
GSM901916
[604]
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[605]
GSM901918
[606]
GSM901919
[607]
GSM901920
[608]
GSM901921
[609]
GSM901922
[610]
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[611]
GSM901924
[612]
GSM901925
[613]
GSM901926
[614]
GSM901927
[615]
GSM901928
[616]
GSM901929
[617]
GSM901930
[618]
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[619]
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[620]
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[621]
GSM901934
[622]
GSM901935
[623]
GSM901936
[624]
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[625]
GSM901938
[626]
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[627]
GSM901940
[628]
GSM901941
[629]
GSM901942
[630]
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[631]
GSM901944
[632]
GSM901945
[633]
GSM901946
[634]
GSM901947
[635]
GSM901948
[636]
GSM901949
[637]
GSM901950
[638]
GSM901951
[639]
GSM901952
[640]
GSM901953
[641]
GSM901954
[642]
GSM901955
[643]
GSM901956
[644]
GSM901957
[645]
GSM901958
[646]
GSM901959
[647]
GSM901960
[648]
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[649]
GSM901962
[650]
GSM901963
[651]
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[652]
GSM901965
[653]
GSM901966
[654]
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[655]
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[656]
GSM901969
[657]
GSM901970
[658]
GSM901971
[659]
GSM901972
[660]
GSM901973
[661]
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[662]
GSM901975
[663]
GSM901976
[664]
GSM901977
[665]
GSM901978
[666]
GSM901979
[667]
GSM901980
[668]
GSM901981
[669]
GSM901982
[670]
GSM901983
[671]
GSM901984
[672]
GSM901985
[673]
GSM901986
[674]
GSM901987
[675]
GSM901988
[676]
GSM901989
[677]
GSM901990
[678]
GSM901991
[679]
GSM901992
[680]
GSM901993
[681]
GSM901994
[682]
GSM901995
[683]
GSM901996
[684]
GSM901997
[685]
GSM901998
[686]
GSM901999
[687]
GSM902000
[688]
GSM902001
[689]
GSM902002
[690]
GSM902003
[691]
GSM902004
[692]
GSM902005
[693]
GSM902006
[694]
GSM902007
[695]
GSM902008
[696]
GSM902009
[697]
GSM902010
[698]
GSM902011
[699]
GSM902012
[700]
GSM902013
[701]
GSM902014
[702]
GSM902015
[703]
GSM902016
[704]
GSM902017
[705]
GSM902018
[706]
GSM902019
[707]
GSM902020
[708]
GSM902021
[709]
GSM902022
[710]
GSM902023
[711]
GSM902024
[712]
GSM902025
[713]
GSM902026
[714]
GSM902027
[715]
GSM902028
[716]
GSM902029
[717]
GSM902030
[718]
GSM902031
[719]
GSM902032
[720]
GSM902033
[721]
GSM902034
[722]
GSM902035
[723]
GSM902036
[724]
GSM902037
[725]
GSM902038
[726]
GSM902039
[727]
GSM902040
[728]
GSM902041
[729]
GSM902042
[730]
GSM902043
[731]
GSM902044
[732]
GSM902045
[733]
GSM902046
[734]
GSM902047
[735]
GSM902048
[736]
GSM902049
[737]
GSM902050
[738]
GSM902051
[739]
GSM902052
[740]
GSM902053
[741]
GSM902054
[742]
GSM902055
[743]
GSM902056
[744]
GSM902057
[745]
GSM902058
[746]
GSM902059
[747]
GSM902060
[748]
GSM902061
[749]
GSM902062
[750]
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[751]
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[752]
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[753]
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[754]
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[755]
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[756]
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[757]
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[758]
GSM902071
[759]
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[760]
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[761]
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[762]
GSM902075
[763]
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[764]
GSM902077
[765]
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[766]
GSM902079
[767]
GSM902080
[768]
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[769]
GSM902082
[770]
GSM902083
[771]
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[772]
GSM902085
[773]
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[774]
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[775]
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[776]
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[777]
GSM902090
[778]
GSM902091
[779]
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sample_count
857
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
A genomic storm in critically injured humans
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE37069
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=GSE37069
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE37069
version
null
note
This study thus included all available microarray-based blood samples of trauma-related GEO data series GSE36809 [29]. After careful examination of the associated metadata, we could identify 185 individuals in total with severe blunt trauma besides the 35 healthy controls in the data series.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
This study thus included all available microarray-based blood samples of trauma-related GEO data series GSE36809 [29]. After careful examination of the associated metadata, we could identify 185 individuals in total with severe blunt trauma besides the 35 healthy controls in the data series.
access_statement_kind
repository_route_statement
sample_accessions array · 590 items
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Gene response to major burn injuries
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title
Prospective randomized doubleblind assessment of transcriptome modulation by hydrocortisone in severe burn shock
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Diagnostic classification by machine learning
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This study thus included all available microarray-based blood samples of trauma-related GEO data series GSE36809 [29]. After careful examination of the associated metadata, we could identify 185 individuals in total with severe blunt trauma besides the 35 healthy controls in the data series.
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[0]
ogies for accurate diagnosis of sepsis using microarray gene expression data.
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-level sample classification of sepsis using microarray gene expression data merged by in silico met
[2]
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Publicly available data series were extracted from NCBI Gene Expression Omnibus and EMBL-EBI ArrayExpress to create a comprehensive meta-analysis microarray expression set (meta-expression set). Measurements had to be obtained via microarray-technique from whole blood samples of adult or pediatric patients with sepsis diagnosed based on international consensus definition immediately after admission to the intensive care unit. We aggregate trauma patients, systemic inflammatory response syndrome (SIRS) patients, and healthy controls in a non-septic entity. Differential expression (DE) analysis is compared with machine-learning-based solutions like decision tree (DT), random forest (RF), support vector machine (SVM), and deep-learning neural networks (DNNs). We evaluated classifier training and discrimination performance in 100 independent iterations. To test diagnostic resilience, we gradually degraded expression data in multiple levels. 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"GSM901906", "GSM901907", "GSM901908", "GSM901909", "GSM901910", "GSM901911", "GSM901912", "GSM901913", "GSM901914", "GSM901915", "GSM901916", "GSM901917", "GSM901918", "GSM901919", "GSM901920", "GSM901921", "GSM901922", "GSM901923", "GSM901924", "GSM901925", "GSM901926", "GSM901927", "GSM901928", "GSM901929", "GSM901930", "GSM901931", "GSM901932", "GSM901933", "GSM901934", "GSM901935", "GSM901936", "GSM901937", "GSM901938", "GSM901939", "GSM901940", "GSM901941", "GSM901942", "GSM901943", "GSM901944", "GSM901945", "GSM901946", "GSM901947", "GSM901948", "GSM901949", "GSM901950", "GSM901951", "GSM901952", "GSM901953", "GSM901954", "GSM901955", "GSM901956", "GSM901957", "GSM901958", "GSM901959", "GSM901960", "GSM901961", "GSM901962", "GSM901963", "GSM901964", "GSM901965", "GSM901966", "GSM901967", "GSM901968", "GSM901969", "GSM901970", "GSM901971", "GSM901972", "GSM901973", "GSM901974", "GSM901975", "GSM901976", "GSM901977", "GSM901978", "GSM901979", "GSM901980", "GSM901981", "GSM901982", "GSM901983", "GSM901984", "GSM901985", "GSM901986", "GSM901987", "GSM901988", "GSM901989", "GSM901990", "GSM901991", "GSM901992", "GSM901993", "GSM901994", "GSM901995", "GSM901996", "GSM901997", "GSM901998", "GSM901999", "GSM902000", "GSM902001", "GSM902002", "GSM902003", "GSM902004", "GSM902005", "GSM902006", "GSM902007", "GSM902008", "GSM902009", "GSM902010", "GSM902011", "GSM902012", "GSM902013", "GSM902014", "GSM902015", "GSM902016", "GSM902017", "GSM902018", "GSM902019", "GSM902020", "GSM902021", "GSM902022", "GSM902023", "GSM902024", "GSM902025", "GSM902026", "GSM902027", "GSM902028", "GSM902029", "GSM902030", "GSM902031", "GSM902032", "GSM902033", "GSM902034", "GSM902035", "GSM902036", "GSM902037", "GSM902038", "GSM902039", "GSM902040", "GSM902041", "GSM902042", "GSM902043", "GSM902044", "GSM902045", "GSM902046", "GSM902047", "GSM902048", "GSM902049", "GSM902050", "GSM902051", "GSM902052", "GSM902053", "GSM902054", "GSM902055", "GSM902056", "GSM902057", "GSM902058", "GSM902059", "GSM902060", "GSM902061", "GSM902062", "GSM902063", "GSM902064", "GSM902065", "GSM902066", "GSM902067", "GSM902068", "GSM902069", "GSM902070", "GSM902071", "GSM902072", "GSM902073", "GSM902074", "GSM902075", "GSM902076", "GSM902077", "GSM902078", "GSM902079", "GSM902080", "GSM902081", "GSM902082", "GSM902083", "GSM902084", "GSM902085", "GSM902086", "GSM902087", "GSM902088", "GSM902089", "GSM902090", "GSM902091", "GSM902092", "GSM902093", "GSM902094", "GSM902095", "GSM902096", "GSM902097", "GSM902098", "GSM902099", "GSM902100", "GSM902101", "GSM902102", "GSM902103", "GSM902104", "GSM902105", "GSM902106", "GSM902107", "GSM902108", "GSM902109", "GSM902110", "GSM902111", "GSM902112", "GSM902113", "GSM902114", "GSM902115", "GSM902116", "GSM902117", "GSM902118", "GSM902119", "GSM902120", "GSM902121", "GSM902122", "GSM902123", "GSM902124", "GSM902125", "GSM902126", "GSM902127", "GSM902128", "GSM902129", "GSM902130", "GSM902131", "GSM902132", "GSM902133", "GSM902134", "GSM902135", "GSM902136", "GSM902137", "GSM902138", "GSM902139", "GSM902140", "GSM902141", "GSM902142", "GSM902143", "GSM902144", "GSM902145", "GSM902146", "GSM902147", "GSM902148", "GSM902149", "GSM902150", "GSM902151", "GSM902152", "GSM902153", "GSM902154", "GSM902155", "GSM902156", "GSM902157", "GSM902158", "GSM902159", "GSM902160", "GSM902161", "GSM902162", "GSM902163", "GSM902164", "GSM902165", "GSM902166", "GSM902167", "GSM902168", "GSM902169"], "sample_count": 857, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "A genomic storm in critically injured humans", "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:GSE37069", "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=GSE37069", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE37069", "version": null, "note": "This study thus included all available microarray-based blood samples of trauma-related GEO data series GSE36809 [29]. After careful examination of the associated metadata, we could identify 185 individuals in total with severe blunt trauma besides the 35 healthy controls in the data series.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "This study thus included all available microarray-based blood samples of trauma-related GEO data series GSE36809 [29]. After careful examination of the associated metadata, we could identify 185 individuals in total with severe blunt trauma besides the 35 healthy controls in the data series.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM909644", "GSM909645", "GSM909646", "GSM909647", "GSM909648", "GSM909649", "GSM909650", "GSM909651", "GSM909652", "GSM909653", "GSM909654", "GSM909655", "GSM909656", "GSM909657", "GSM909658", "GSM909659", "GSM909660", "GSM909661", "GSM909662", "GSM909663", "GSM909664", "GSM909665", "GSM909666", "GSM909667", "GSM909668", "GSM909669", "GSM909670", "GSM909671", "GSM909672", "GSM909673", "GSM909674", "GSM909675", "GSM909676", "GSM909677", "GSM909678", "GSM909679", "GSM909680", "GSM909681", "GSM909682", "GSM909683", "GSM909684", "GSM909685", "GSM909686", "GSM909687", "GSM909688", "GSM909689", "GSM909690", "GSM909691", "GSM909692", "GSM909693", "GSM909694", "GSM909695", "GSM909696", "GSM909697", "GSM909698", "GSM909699", "GSM909700", "GSM909701", "GSM909702", "GSM909703", "GSM909704", "GSM909705", "GSM909706", "GSM909707", "GSM909708", "GSM909709", "GSM909710", "GSM909711", "GSM909712", "GSM909713", "GSM909714", "GSM909715", "GSM909716", "GSM909717", "GSM909718", "GSM909719", "GSM909720", "GSM909721", "GSM909722", "GSM909723", "GSM909724", "GSM909725", "GSM909726", "GSM909727", "GSM909728", "GSM909729", "GSM909730", "GSM909731", "GSM909732", "GSM909733", "GSM909734", "GSM909735", "GSM909736", "GSM909737", "GSM909738", "GSM909739", "GSM909740", "GSM909741", "GSM909742", "GSM909743", "GSM909744", "GSM909745", "GSM909746", "GSM909747", "GSM909748", "GSM909749", "GSM909750", "GSM909751", "GSM909752", "GSM909753", "GSM909754", "GSM909755", "GSM909756", "GSM909757", "GSM909758", "GSM909759", "GSM909760", "GSM909761", "GSM909762", "GSM909763", "GSM909764", "GSM909765", "GSM909766", "GSM909767", "GSM909768", "GSM909769", "GSM909770", "GSM909771", "GSM909772", "GSM909773", "GSM909774", "GSM909775", "GSM909776", "GSM909777", "GSM909778", "GSM909779", "GSM909780", "GSM909781", "GSM909782", "GSM909783", "GSM909784", "GSM909785", "GSM909786", "GSM909787", "GSM909788", "GSM909789", "GSM909790", "GSM909791", "GSM909792", "GSM909793", "GSM909794", "GSM909795", "GSM909796", "GSM909797", "GSM909798", "GSM909799", "GSM909800", "GSM909801", "GSM909802", "GSM909803", "GSM909804", "GSM909805", "GSM909806", "GSM909807", "GSM909808", "GSM909809", "GSM909810", "GSM909811", "GSM909812", "GSM909813", "GSM909814", "GSM909815", "GSM909816", "GSM909817", "GSM909818", "GSM909819", "GSM909820", "GSM909821", "GSM909822", "GSM909823", "GSM909824", "GSM909825", "GSM909826", "GSM909827", "GSM909828", "GSM909829", "GSM909830", "GSM909831", "GSM909832", "GSM909833", "GSM909834", "GSM909835", "GSM909836", "GSM909837", "GSM909838", "GSM909839", "GSM909840", "GSM909841", "GSM909842", "GSM909843", "GSM909844", "GSM909845", "GSM909846", "GSM909847", "GSM909848", "GSM909849", "GSM909850", "GSM909851", "GSM909852", "GSM909853", "GSM909854", "GSM909855", "GSM909856", "GSM909857", "GSM909858", "GSM909859", "GSM909860", "GSM909861", "GSM909862", "GSM909863", "GSM909864", "GSM909865", "GSM909866", "GSM909867", "GSM909868", "GSM909869", "GSM909870", "GSM909871", "GSM909872", "GSM909873", "GSM909874", "GSM909875", "GSM909876", "GSM909877", "GSM909878", "GSM909879", "GSM909880", "GSM909881", "GSM909882", "GSM909883", "GSM909884", "GSM909885", "GSM909886", "GSM909887", "GSM909888", "GSM909889", "GSM909890", "GSM909891", "GSM909892", "GSM909893", "GSM909894", "GSM909895", "GSM909896", "GSM909897", "GSM909898", "GSM909899", "GSM909900", "GSM909901", "GSM909902", "GSM909903", "GSM909904", "GSM909905", "GSM909906", "GSM909907", "GSM909908", "GSM909909", "GSM909910", "GSM909911", "GSM909912", "GSM909913", "GSM909914", "GSM909915", "GSM909916", "GSM909917", "GSM909918", "GSM909919", "GSM909920", "GSM909921", "GSM909922", "GSM909923", "GSM909924", "GSM909925", "GSM909926", "GSM909927", "GSM909928", "GSM909929", "GSM909930", "GSM909931", "GSM909932", "GSM909933", "GSM909934", "GSM909935", "GSM909936", "GSM909937", "GSM909938", "GSM909939", "GSM909940", "GSM909941", "GSM909942", "GSM909943", "GSM909944", "GSM909945", "GSM909946", "GSM909947", "GSM909948", "GSM909949", "GSM909950", "GSM909951", "GSM909952", "GSM909953", "GSM909954", "GSM909955", "GSM909956", "GSM909957", "GSM909958", "GSM909959", "GSM909960", "GSM909961", "GSM909962", "GSM909963", "GSM909964", "GSM909965", "GSM909966", "GSM909967", "GSM909968", "GSM909969", "GSM909970", "GSM909971", "GSM909972", "GSM909973", "GSM909974", "GSM909975", "GSM909976", "GSM909977", "GSM909978", "GSM909979", "GSM909980", "GSM909981", "GSM909982", "GSM909983", "GSM909984", "GSM909985", "GSM909986", "GSM909987", "GSM909988", "GSM909989", "GSM909990", "GSM909991", "GSM909992", "GSM909993", "GSM909994", "GSM909995", "GSM909996", "GSM909997", "GSM909998", "GSM909999", "GSM910000", "GSM910001", "GSM910002", "GSM910003", "GSM910004", "GSM910005", "GSM910006", "GSM910007", "GSM910008", "GSM910009", "GSM910010", "GSM910011", "GSM910012", "GSM910013", "GSM910014", "GSM910015", "GSM910016", "GSM910017", "GSM910018", "GSM910019", "GSM910020", "GSM910021", "GSM910022", "GSM910023", "GSM910024", "GSM910025", "GSM910026", "GSM910027", "GSM910028", "GSM910029", "GSM910030", "GSM910031", "GSM910032", "GSM910033", "GSM910034", "GSM910035", "GSM910036", "GSM910037", "GSM910038", "GSM910039", "GSM910040", "GSM910041", "GSM910042", "GSM910043", "GSM910044", "GSM910045", "GSM910046", "GSM910047", "GSM910048", "GSM910049", "GSM910050", "GSM910051", "GSM910052", "GSM910053", "GSM910054", "GSM910055", "GSM910056", "GSM910057", "GSM910058", "GSM910059", "GSM910060", "GSM910061", "GSM910062", "GSM910063", "GSM910064", "GSM910065", "GSM910066", "GSM910067", "GSM910068", "GSM910069", "GSM910070", "GSM910071", "GSM910072", "GSM910073", "GSM910074", "GSM910075", "GSM910076", "GSM910077", "GSM910078", "GSM910079", "GSM910080", "GSM910081", "GSM910082", "GSM910083", "GSM910084", "GSM910085", "GSM910086", "GSM910087", "GSM910088", "GSM910089", "GSM910090", "GSM910091", "GSM910092", "GSM910093", "GSM910094", "GSM910095", "GSM910096", "GSM910097", "GSM910098", "GSM910099", "GSM910100", "GSM910101", "GSM910102", "GSM910103", "GSM910104", "GSM910105", "GSM910106", "GSM910107", "GSM910108", "GSM910109", "GSM910110", "GSM910111", "GSM910112", "GSM910113", "GSM910114", "GSM910115", "GSM910116", "GSM910117", "GSM910118", "GSM910119", "GSM910120", "GSM910121", "GSM910122", "GSM910123", "GSM910124", "GSM910125", "GSM910126", "GSM910127", "GSM910128", "GSM910129", "GSM910130", "GSM910131", "GSM910132", "GSM910133", "GSM910134", "GSM910135", "GSM910136", "GSM910137", "GSM910138", "GSM910139", "GSM910140", "GSM910141", "GSM910142", "GSM910143", "GSM910144", "GSM910145", "GSM910146", "GSM910147", "GSM910148", "GSM910149", "GSM910150", "GSM910151", "GSM910152", "GSM910153", "GSM910154", "GSM910155", "GSM910156", "GSM910157", "GSM910158", "GSM910159", "GSM910160", "GSM910161", "GSM910162", "GSM910163", "GSM910164", "GSM910165", "GSM910166", "GSM910167", "GSM910168", "GSM910169", "GSM910170", "GSM910171", "GSM910172", "GSM910173", "GSM910174", "GSM910175", "GSM910176", "GSM910177", "GSM910178", "GSM910179", "GSM910180", "GSM910181", "GSM910182", "GSM910183", "GSM910184", "GSM910185", "GSM910186", "GSM910187", "GSM910188", "GSM910189", "GSM910190", "GSM910191", "GSM910192", "GSM910193", "GSM910194", "GSM910195", "GSM910196", "GSM910197", "GSM910198", "GSM910199", "GSM910200", "GSM910201", "GSM910202", "GSM910203", "GSM910204", "GSM910205", "GSM910206", "GSM910207", "GSM910208", "GSM910209", "GSM910210", "GSM910211", "GSM910212", "GSM910213", "GSM910214", "GSM910215", "GSM910216", "GSM910217", "GSM910218", "GSM910219", "GSM910220", "GSM910221", "GSM910222", "GSM910223", "GSM910224", "GSM910225", "GSM910226", "GSM910227", "GSM910228", "GSM910229", "GSM910230", "GSM910231", "GSM910232", "GSM910233"], "sample_count": 590, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gene response to major burn injuries", "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:GSE77791", "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=GSE77791", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE77791", "version": null, "note": "This study thus included all available microarray-based blood samples of trauma-related GEO data series GSE36809 [29]. After careful examination of the associated metadata, we could identify 185 individuals in total with severe blunt trauma besides the 35 healthy controls in the data series.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "This study thus included all available microarray-based blood samples of trauma-related GEO data series GSE36809 [29]. After careful examination of the associated metadata, we could identify 185 individuals in total with severe blunt trauma besides the 35 healthy controls in the data series.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM2059436", "GSM2059437", "GSM2059438", "GSM2059439", "GSM2059440", "GSM2059441", "GSM2059442", "GSM2059443", "GSM2059444", "GSM2059445", "GSM2059446", "GSM2059447", "GSM2059448", "GSM2059449", "GSM2059450", "GSM2059451", "GSM2059452", "GSM2059453", "GSM2059454", "GSM2059455", "GSM2059456", "GSM2059457", "GSM2059458", "GSM2059459", "GSM2059460", "GSM2059461", "GSM2059462", "GSM2059463", "GSM2059464", "GSM2059465", "GSM2059466", "GSM2059467", "GSM2059468", "GSM2059469", "GSM2059470", "GSM2059471", "GSM2059472", "GSM2059473", "GSM2059474", "GSM2059475", "GSM2059476", "GSM2059477", "GSM2059478", "GSM2059479", "GSM2059480", "GSM2059481", "GSM2059482", "GSM2059483", "GSM2059484", "GSM2059485", "GSM2059486", "GSM2059487", "GSM2059488", 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