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pmid:35273684

Integrated analysis of differentially expressed genes and a ceRNA network to identify hub lncRNAs and potential drugs for multiple sclerosis.

Tianfeng Wang · Si Xu · Li Liu · Shuang Li · Huixue Zhang · Xiaoyu Lu · Xiaotong Kong · Danyang Li · Jianjian Wang · Lihua Wang

American journal of translational research · 2022

Paper

partial

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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Integrated analysis of differentially expressed genes and a ceRNA network to identify hub lncRNAs and potential drugs for multiple sclerosis.
doi
null
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35273684
authors array · 10 items
[0]
Tianfeng Wang
[1]
Si Xu
[2]
Li Liu
[3]
Shuang Li
[4]
Huixue Zhang
[5]
Xiaoyu Lu
[6]
Xiaotong Kong
[7]
Danyang Li
[8]
Jianjian Wang
[9]
Lihua Wang
journal
American journal of translational research
year
2022
abstract
OBJECTIVE: Multiple sclerosis (MS) is an autoimmune neuroinflammatory disease of the nervous system. However, the precise molecular mechanisms underlying MS have yet to be fully elucidated. In this study, our aim was to provide novel insight into the pathogenesis of MS and provide a resource for identifying new biomarkers and therapeutics for MS. METHODS: In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs). Next, we constructed a protein-protein interaction (PPI) network and a MS-specific ceRNA network (MCEN) by integrating expression profiles, interaction pairs of mRNA-miRNAs and lncRNA-miRNAs. Then, according to the modular structure of the PPI network, we identified hub DEmRNAs and generated a ceRNA subnetwork so that we could analyze the key lncRNAs that were associated with MS. RESULTS: We first identified 4 modules by constructing a PPI network using DEmRNAs. Functional enrichment analysis showed these modules were enriched in immune-related pathways. Then, we constructed the MCEN and the hub gene-associated ceRNA subnetwork using a comprehensive computational approach. We identified three key lncRNAs (LINC00649, TP73-AS1 and MALAT1) and further identified key lncRNA-mediated ceRNAs within the subnetwork. Finally, by analyzing LINC00649-miR-1275-CD20, we identified 6 drugs that may represent novel drugs for MS. CONCLUSION: Collectively, our results provide novel insight for the discovery of biomarkers and therapeutics for MS and provide a suitable foundation from which to design future investigations of the pathogenic mechanisms associated with MS.
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In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs).
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We identified three key lncRNAs (LINC00649, TP73-AS1 and MALAT1) and further identified key lncRNA-mediated ceRNAs within the subnetwork.
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Expression data from peripheral blood mononuclear cells in multiple sclerosis patients and controls
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GSM1512551
[414]
GSM1512552
[415]
GSM1512553
[416]
GSM1512554
[417]
GSM1512555
[418]
GSM1512556
[419]
GSM1512557
[420]
GSM1512558
[421]
GSM1512559
[422]
GSM1512560
[423]
GSM1512561
[424]
GSM1512562
[425]
GSM1512563
[426]
GSM1512564
[427]
GSM1512565
[428]
GSM1512566
[429]
GSM1512567
[430]
GSM1512568
[431]
GSM1512569
[432]
GSM1512570
[433]
GSM1512571
[434]
GSM1512572
[435]
GSM1512573
[436]
GSM1512574
[437]
GSM1512575
[438]
GSM1512576
[439]
GSM1512577
[440]
GSM1512578
[441]
GSM1512579
[442]
GSM1512580
[443]
GSM1512581
[444]
GSM1512582
[445]
GSM1512583
[446]
GSM1512584
[447]
GSM1512585
[448]
GSM1512586
[449]
GSM1512587
[450]
GSM1512588
[451]
GSM1512589
[452]
GSM1512590
[453]
GSM1512591
[454]
GSM1512592
[455]
GSM1512593
[456]
GSM1512594
[457]
GSM1512595
[458]
GSM1512596
[459]
GSM1512597
[460]
GSM1512598
[461]
GSM1512599
[462]
GSM1512600
[463]
GSM1512601
[464]
GSM1512602
[465]
GSM1512603
[466]
GSM1512604
[467]
GSM1512605
[468]
GSM1512606
[469]
GSM1512607
[470]
GSM1512608
[471]
GSM1512609
[472]
GSM1512610
[473]
GSM1512611
[474]
GSM1512612
[475]
GSM1512613
[476]
GSM1512614
[477]
GSM1512615
[478]
GSM1512616
[479]
GSM1512617
[480]
GSM1512618
[481]
GSM1512619
[482]
GSM1512620
[483]
GSM1512621
[484]
GSM1512622
[485]
GSM1512623
[486]
GSM1512624
[487]
GSM1512625
[488]
GSM1512626
[489]
GSM1512627
[490]
GSM1512628
[491]
GSM1512629
[492]
GSM1512630
[493]
GSM1512631
[494]
GSM1512632
[495]
GSM1512633
[496]
GSM1512634
[497]
GSM1512635
[498]
GSM1512636
[499]
GSM1512637
[500]
GSM1512638
[501]
GSM1512639
[502]
GSM1512640
[503]
GSM1512641
[504]
GSM1512642
[505]
GSM1512643
[506]
GSM1512644
[507]
GSM1512645
[508]
GSM1512646
[509]
GSM1512647
[510]
GSM1512648
[511]
GSM1512649
[512]
GSM1512650
[513]
GSM1512651
[514]
GSM1512652
[515]
GSM1512653
[516]
GSM1512654
[517]
GSM1512655
[518]
GSM1512656
[519]
GSM1512657
[520]
GSM1512658
[521]
GSM1512659
[522]
GSM1512660
[523]
GSM1512661
[524]
GSM1512662
[525]
GSM1512663
[526]
GSM1512664
[527]
GSM1512665
[528]
GSM1512666
[529]
GSM1512667
[530]
GSM1512668
[531]
GSM1512669
[532]
GSM1512670
[533]
GSM1512671
[534]
GSM1512672
[535]
GSM1512673
[536]
GSM1512674
[537]
GSM1512675
[538]
GSM1512676
[539]
GSM1512677
[540]
GSM1512678
[541]
GSM1512679
[542]
GSM1512680
[543]
GSM1512681
[544]
GSM1512682
[545]
GSM1512683
[546]
GSM1512684
[547]
GSM1512685
[548]
GSM1512686
[549]
GSM1512687
[550]
GSM1512688
[551]
GSM1512689
[552]
GSM1512690
[553]
GSM1512691
[554]
GSM1512692
[555]
GSM1512693
[556]
GSM1512694
[557]
GSM1512695
[558]
GSM1512696
[559]
GSM1512697
[560]
GSM1512698
[561]
GSM1512699
[562]
GSM1512700
[563]
GSM1512701
[564]
GSM1512702
[565]
GSM1512703
[566]
GSM1512704
[567]
GSM1512705
[568]
GSM1512706
[569]
GSM1512707
[570]
GSM1512708
[571]
GSM1512709
[572]
GSM1512710
[573]
GSM1512711
[574]
GSM1512712
[575]
GSM1512713
[576]
GSM1512714
[577]
GSM1512715
[578]
GSM1512716
[579]
GSM1512717
[580]
GSM1512718
[581]
GSM1512719
[582]
GSM1512720
[583]
GSM1512721
[584]
GSM1512722
[585]
GSM1512723
[586]
GSM1512724
[587]
GSM1512725
[588]
GSM1512726
[589]
GSM1512727
[590]
GSM1512728
[591]
GSM1512729
[592]
GSM1512730
[593]
GSM1512731
[594]
GSM1512732
[595]
GSM1512733
[596]
GSM1512734
[597]
GSM1512735
[598]
GSM1512736
[599]
GSM1512737
[600]
GSM1512738
[601]
GSM1512739
[602]
GSM1512740
[603]
GSM1512741
[604]
GSM1512742
[605]
GSM1512743
[606]
GSM1512744
[607]
GSM1512745
[608]
GSM1512746
[609]
GSM1512747
[610]
GSM1512748
[611]
GSM1512749
[612]
GSM1512750
[613]
GSM1512751
[614]
GSM1512752
[615]
GSM1512753
[616]
GSM1512754
[617]
GSM1512755
[618]
GSM1512756
[619]
GSM1512757
[620]
GSM1512758
[621]
GSM1512759
[622]
GSM1512760
[623]
GSM1512761
[624]
GSM1512762
[625]
GSM1512763
[626]
GSM1512764
[627]
GSM1512765
[628]
GSM1512766
[629]
GSM1512767
[630]
GSM1512768
[631]
GSM1512769
[632]
GSM1512770
[633]
GSM1512771
[634]
GSM1512772
[635]
GSM1512773
[636]
GSM1512774
[637]
GSM1512775
[638]
GSM1512776
[639]
GSM1512777
[640]
GSM1512778
[641]
GSM1512779
[642]
GSM1512780
[643]
GSM1512781
[644]
GSM1512782
[645]
GSM1512783
[646]
GSM1512784
[647]
GSM1512785
[648]
GSM1512786
[649]
GSM1512787
[650]
GSM1512788
[651]
GSM1512789
[652]
GSM1512790
[653]
GSM1512791
[654]
GSM1512792
[655]
GSM1512793
[656]
GSM1512794
[657]
GSM1512795
[658]
GSM1512796
[659]
GSM1512797
[660]
GSM1512798
[661]
GSM1512799
[662]
GSM1512800
[663]
GSM1512801
[664]
GSM1512802
[665]
GSM1512803
[666]
GSM1512804
[667]
GSM1512805
[668]
GSM1512806
[669]
GSM1512807
[670]
GSM1512808
[671]
GSM1512809
[672]
GSM1512810
[673]
GSM1512811
[674]
GSM1512812
[675]
GSM1512813
[676]
GSM1512814
[677]
GSM1512815
[678]
GSM1512816
[679]
GSM1512817
[680]
GSM1512818
[681]
GSM1512819
[682]
GSM1512820
[683]
GSM1512821
[684]
GSM1512822
[685]
GSM1512823
[686]
GSM1512824
[687]
GSM1512825
[688]
GSM1512826
[689]
GSM1512827
[690]
GSM1512828
[691]
GSM1512829
[692]
GSM1512830
[693]
GSM1512831
[694]
GSM1512832
[695]
GSM1512833
[696]
GSM1512834
[697]
GSM1512835
[698]
GSM1512836
[699]
GSM1512837
[700]
GSM1512838
[701]
GSM1512839
[702]
GSM1512840
[703]
GSM1512841
[704]
GSM1512842
[705]
GSM1512843
[706]
GSM1512844
[707]
GSM1512845
[708]
GSM1512846
[709]
GSM1512847
[710]
GSM1512848
[711]
GSM1512849
[712]
GSM1512850
[713]
GSM1512851
[714]
GSM1512852
[715]
GSM1512853
[716]
GSM1512854
[717]
GSM1512855
[718]
GSM1512856
[719]
GSM1512857
[720]
GSM1512858
[721]
GSM1512859
[722]
GSM1512860
[723]
GSM1512861
[724]
GSM1512862
[725]
GSM1512863
[726]
GSM1512864
[727]
GSM1512865
[728]
GSM1512866
[729]
GSM1512867
[730]
GSM1512868
[731]
GSM1512869
[732]
GSM1512870
[733]
GSM1512871
[734]
GSM1512872
[735]
GSM1512873
[736]
GSM1512874
[737]
GSM1512875
[738]
GSM1512876
[739]
GSM1512877
[740]
GSM1512878
[741]
GSM1512879
[742]
GSM1512880
[743]
GSM1512881
[744]
GSM1512882
[745]
GSM1512883
[746]
GSM1512884
[747]
GSM1512885
[748]
GSM1512886
[749]
GSM1512887
[750]
GSM1512888
[751]
GSM1512889
[752]
GSM1512890
[753]
GSM1512891
[754]
GSM1512892
[755]
GSM1512893
[756]
GSM1512894
[757]
GSM1512895
[758]
GSM1512896
[759]
GSM1512897
[760]
GSM1512898
[761]
GSM1512899
[762]
GSM1512900
[763]
GSM1512901
[764]
GSM1512902
[765]
GSM1512903
[766]
GSM1512904
[767]
GSM1512905
[768]
GSM1512906
[769]
GSM1512907
[770]
GSM1512908
[771]
GSM1512909
[772]
GSM1512910
[773]
GSM1512911
[774]
GSM1512912
[775]
GSM1512913
[776]
GSM1512914
[777]
GSM1512915
[778]
GSM1512916
[779]
GSM1512917
[780]
GSM1512918
[781]
GSM1512919
[782]
GSM1512920
[783]
GSM1512921
[784]
GSM1512922
[785]
GSM1512923
[786]
GSM1512924
[787]
GSM1512925
[788]
GSM1512926
[789]
GSM1512927
[790]
GSM1512928
[791]
GSM1512929
[792]
GSM1512930
[793]
GSM1512931
[794]
GSM1512932
[795]
GSM1512933
[796]
GSM1512934
[797]
GSM1512935
[798]
GSM1512936
[799]
GSM1512937
[800]
GSM1512938
[801]
GSM1512939
[802]
GSM1512940
[803]
GSM1512941
[804]
GSM1512942
[805]
GSM1512943
[806]
GSM1512944
[807]
GSM1512945
[808]
GSM1512946
[809]
GSM1512947
[810]
GSM1512948
[811]
GSM1512949
[812]
GSM1512950
[813]
GSM1512951
[814]
GSM1512952
[815]
GSM1512953
[816]
GSM1512954
[817]
GSM1512955
[818]
GSM1512956
[819]
GSM1512957
[820]
GSM1512958
[821]
GSM1512959
[822]
GSM1512960
[823]
GSM1512961
[824]
GSM1512962
[825]
GSM1512963
[826]
GSM1512964
[827]
GSM1512965
[828]
GSM1512966
[829]
GSM1512967
[830]
GSM1512968
[831]
GSM1512969
[832]
GSM1512970
[833]
GSM1512971
[834]
GSM1512972
[835]
GSM1512973
[836]
GSM1512974
[837]
GSM1512975
[838]
GSM1512976
[839]
GSM1512977
[840]
GSM1512978
[841]
GSM1512979
[842]
GSM1512980
[843]
GSM1512981
[844]
GSM1512982
[845]
GSM1512983
[846]
GSM1512984
[847]
GSM1512985
[848]
GSM1512986
[849]
GSM1512987
[850]
GSM1512988
[851]
GSM1512989
[852]
GSM1512990
[853]
GSM1512991
[854]
GSM1512992
[855]
GSM1512993
[856]
GSM1512994
[857]
GSM1512995
[858]
GSM1512996
[859]
GSM1512997
[860]
GSM1512998
[861]
GSM1512999
[862]
GSM1513000
[863]
GSM1513001
[864]
GSM1513002
[865]
GSM1513003
[866]
GSM1513004
[867]
GSM1513005
[868]
GSM1513006
[869]
GSM1513007
[870]
GSM1513008
[871]
GSM1513009
[872]
GSM1513010
[873]
GSM1513011
[874]
GSM1513012
[875]
GSM1513013
[876]
GSM1513014
[877]
GSM1513015
[878]
GSM1513016
[879]
GSM1513017
[880]
GSM1513018
[881]
GSM1513019
[882]
GSM1513020
[883]
GSM1513021
[884]
GSM1513022
[885]
GSM1513023
[886]
GSM1513024
[887]
GSM1513025
[888]
GSM1513026
[889]
GSM1513027
[890]
GSM1513028
[891]
GSM1513029
[892]
GSM1513030
[893]
GSM1513031
[894]
GSM1513032
[895]
GSM1513033
[896]
GSM1513034
[897]
GSM1513035
[898]
GSM1513036
[899]
GSM1513037
[900]
GSM1513038
[901]
GSM1513039
[902]
GSM1513040
[903]
GSM1513041
[904]
GSM1513042
[905]
GSM1513043
[906]
GSM1513044
[907]
GSM1513045
[908]
GSM1513046
[909]
GSM1513047
[910]
GSM1513048
[911]
GSM1513049
[912]
GSM1513050
[913]
GSM1513051
[914]
GSM1513052
[915]
GSM1513053
[916]
GSM1513054
[917]
GSM1513055
[918]
GSM1513056
[919]
GSM1513057
[920]
GSM1513058
[921]
GSM1513059
[922]
GSM1513060
[923]
GSM1513061
[924]
GSM1513062
[925]
GSM1513063
[926]
GSM1513064
[927]
GSM1513065
[928]
GSM1513066
[929]
GSM1513067
[930]
GSM1513068
[931]
GSM1513069
[932]
GSM1513070
[933]
GSM1513071
[934]
GSM1513072
[935]
GSM1513073
[936]
GSM1513074
[937]
GSM1513075
[938]
GSM1513076
[939]
GSM1513077
[940]
GSM1513078
[941]
GSM1513079
[942]
GSM1513080
[943]
GSM1513081
[944]
GSM1513082
[945]
GSM1513083
[946]
GSM1513084
[947]
GSM1513085
[948]
GSM1513086
[949]
GSM1513087
[950]
GSM1513088
[951]
GSM1513089
[952]
GSM1513090
[953]
GSM1513091
[954]
GSM1513092
[955]
GSM1513093
[956]
GSM1513094
[957]
GSM1513095
[958]
GSM1513096
[959]
GSM1513097
[960]
GSM1513098
[961]
GSM1513099
[962]
GSM1513100
[963]
GSM1513101
[964]
GSM1513102
[965]
GSM1513103
[966]
GSM1513104
[967]
GSM1513105
[968]
GSM1513106
[969]
GSM1513107
[970]
GSM1513108
[971]
GSM1513109
[972]
GSM1513110
[973]
GSM1513111
[974]
GSM1513112
[975]
GSM1513113
[976]
GSM1513114
[977]
GSM1513115
[978]
GSM1513116
[979]
GSM1513117
[980]
GSM1513118
[981]
GSM1513119
[982]
GSM1513120
[983]
GSM1513121
[984]
GSM1513122
[985]
GSM1513123
[986]
GSM1513124
[987]
GSM1513125
[988]
GSM1513126
[989]
GSM1513127
[990]
GSM1513128
[991]
GSM1513129
[992]
GSM1513130
[993]
GSM1513131
[994]
GSM1513132
[995]
GSM1513133
[996]
GSM1513134
[997]
GSM1513135
[998]
GSM1513136
[999]
GSM1513137
[1000]
GSM1513138
[1001]
GSM1513139
[1002]
GSM1513140
[1003]
GSM1513141
[1004]
GSM1513142
[1005]
GSM1513143
[1006]
GSM1513144
[1007]
GSM1513145
[1008]
GSM1513146
[1009]
GSM1513147
[1010]
GSM1513148
[1011]
GSM1513149
[1012]
GSM1513150
[1013]
GSM1513151
[1014]
GSM1513152
[1015]
GSM1513153
[1016]
GSM1513154
[1017]
GSM1513155
[1018]
GSM1513156
[1019]
GSM1513157
[1020]
GSM1513158
[1021]
GSM1513159
[1022]
GSM1513160
[1023]
GSM1513161
[1024]
GSM1513162
[1025]
GSM1513163
[1026]
GSM1513164
[1027]
GSM1513165
[1028]
GSM1513166
[1029]
GSM1513167
[1030]
GSM1513168
[1031]
GSM1513169
[1032]
GSM1513170
[1033]
GSM1513171
[1034]
GSM1513172
[1035]
GSM1513173
[1036]
GSM1513174
[1037]
GSM1513175
[1038]
GSM1513176
[1039]
GSM1513177
[1040]
GSM1513178
[1041]
GSM1513179
[1042]
GSM1513180
[1043]
GSM1513181
[1044]
GSM1513182
[1045]
GSM1513183
[1046]
GSM1513184
[1047]
GSM1513185
[1048]
GSM1513186
sample_count
1049
group_sizes
null
group_sizes_basis
null
platform
9040
taxon
Homo sapiens
title
miRNA Profiles in patients and controls
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 · 4 items
[0]
asset:data:geo:GSE21942 not downloaded
[1]
asset:data:geo:GSE21942 licence not read
[2]
asset:data:geo:GSE61741 not downloaded
[3]
asset:data:geo:GSE61741 licence not read
analysis object · 4 fields
state
complete
methods array · 1 item
[0] object · 10 fields
id
method-1
family
network_analysis
specific
ppi_network
label
Network / pathway analysis
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
protein-protein interaction
targets array · 0 items
gaps array · 0 items
capability object · 3 fields
state
complete
requirements array · 1 item
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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
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nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 3 items
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build_graph
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centrality_scores
[2]
pathway_enrich
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basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: ppi_network.
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 · 2 items
[0]
GSE21942
[1]
GSE61741
resolved_accessions array · 2 items
[0]
GSE21942
[1]
GSE61741
statements array · 1 item
[0]
In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs).
basis
The paper names GSE21942, GSE61741 in GEO database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
assets array · 2 items
[0]
source:pmid:35273684
[1]
data:geo:GSE21942
steps array · 1 item
[0]
run_analysis
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE21942
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
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MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-11-01T17:37:17Z
independence
single_reader
evidence_check object · 2 fields
method
null
availability
null
calls
5
usage object · 3 fields
prompt_tokens
2003
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789
cached_tokens
128
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id
extraction
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complete
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MiniMax-M3.1-Flash
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minimax
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review.human_critique
execution object · 5 fields
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absent
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null
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gaps array · 1 item
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provenance object · 7 fields
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pmid:35273684
type
paper
label
pmid:35273684
[1] object · 3 fields
id
source:pmid:35273684
type
manuscript
label
PMID 35273684 full text
[2] object · 3 fields
id
data:geo:GSE21942
type
dataset
label
GEO GSE21942
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:35273684
type
paper
label
pmid:35273684
[1] object · 3 fields
id
source:pmid:35273684
type
manuscript
label
PMID 35273684 full text
[2] object · 3 fields
id
data:geo:GSE21942
type
dataset
label
GEO GSE21942
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-35273684
type
extraction
used array · 1 item
[0]
source:pmid:35273684
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agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE21942
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accession_resolution
used array · 1 item
[0]
data:geo:GSE21942
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agent:corpus-assay-engine
agents array · 2 items
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agent:corpus-assay-engine
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Corpus assay engine
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agent:minimax-reader
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MiniMax literature reader
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dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
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ba34b49490d9bfaf
lineage object · 4 fields
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pmid:35273684
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sha256:c57419f1d56c83aa20c92424e67a6dac0e83ddad8d13e0b4eb39605ff975623f
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null
gaps array · 9 items
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asset:data:geo:GSE21942 licence not read
[1]
asset:data:geo:GSE21942 not downloaded
[2]
asset:data:geo:GSE61741 licence not read
[3]
asset:data:geo:GSE61741 not downloaded
[4]
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[8]
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assays array · 1 item
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pathway_enrich
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supported
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f2132e96ae6c7a4e
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protein-protein interaction
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35273684", "kind": "science-record", "revision": 4, "content_hash": "sha256:ba1953b7564b78e4e4f01d634d2c676e8f84d146ccfb58d8c1eb3e96e521f243", "created_at": "2026-11-01T18:14:03Z", "updated_at": "2026-11-01T22:06:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "partial", "title": "Integrated analysis of differentially expressed genes and a ceRNA network to identify hub lncRNAs and potential drugs for multiple sclerosis.", "doi": null, "pmid": "35273684", "authors": ["Tianfeng Wang", "Si Xu", "Li Liu", "Shuang Li", "Huixue Zhang", "Xiaoyu Lu", "Xiaotong Kong", "Danyang Li", "Jianjian Wang", "Lihua Wang"], "journal": "American journal of translational research", "year": 2022, "abstract": "OBJECTIVE: Multiple sclerosis (MS) is an autoimmune neuroinflammatory disease of the nervous system. However, the precise molecular mechanisms underlying MS have yet to be fully elucidated. In this study, our aim was to provide novel insight into the pathogenesis of MS and provide a resource for identifying new biomarkers and therapeutics for MS.\nMETHODS: In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs). Next, we constructed a protein-protein interaction (PPI) network and a MS-specific ceRNA network (MCEN) by integrating expression profiles, interaction pairs of mRNA-miRNAs and lncRNA-miRNAs. Then, according to the modular structure of the PPI network, we identified hub DEmRNAs and generated a ceRNA subnetwork so that we could analyze the key lncRNAs that were associated with MS.\nRESULTS: We first identified 4 modules by constructing a PPI network using DEmRNAs. Functional enrichment analysis showed these modules were enriched in immune-related pathways. Then, we constructed the MCEN and the hub gene-associated ceRNA subnetwork using a comprehensive computational approach. We identified three key lncRNAs (LINC00649, TP73-AS1 and MALAT1) and further identified key lncRNA-mediated ceRNAs within the subnetwork. Finally, by analyzing LINC00649-miR-1275-CD20, we identified 6 drugs that may represent novel drugs for MS.\nCONCLUSION: Collectively, our results provide novel insight for the discovery of biomarkers and therapeutics for MS and provide a suitable foundation from which to design future investigations of the pathogenic mechanisms associated with MS.", "claims": [{"id": "claim-data-access", "statement": "In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35273684", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We identified three key lncRNAs (LINC00649, TP73-AS1 and MALAT1) and further identified key lncRNA-mediated ceRNAs within the subnetwork.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35273684", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We identified three key lncRNAs (LINC00649, TP73-AS1 and MALAT1) and further identified key lncRNA-mediated ceRNAs within the subnetwork."}], "state": "complete"}], "gaps": ["doi"]}, "experiment": {"state": "complete", "objective": "We identified three key lncRNAs (LINC00649, TP73-AS1 and MALAT1) and further identified key lncRNA-mediated ceRNAs within the subnetwork.", "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:35273684"], "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:GSE21942"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "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:GSE21942"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35273684", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": null, "sha256": "sha256:8f33aad8f3b20c750968c2ded425bc4c3c5f9ca19ff3ff1e1a27015fbfc65bae", "bytes": 1791, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "35273684", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8902536", "source": "ncbi_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE21942", "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=GSE21942", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE21942", "version": null, "note": "In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs).", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM545818", "GSM545819", "GSM545820", "GSM545821", "GSM545822", "GSM545823", "GSM545824", "GSM545825", "GSM545826", "GSM545827", "GSM545828", "GSM545829", "GSM545830", "GSM545831", "GSM545832", "GSM545833", "GSM545834", "GSM545835", "GSM545836", "GSM545837", "GSM545838", "GSM545839", "GSM545840", "GSM545841", "GSM545842", "GSM545843", "GSM545844", "GSM545845", "GSM545846"], "sample_count": 29, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Expression data from peripheral blood 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"GSM1513182", "GSM1513183", "GSM1513184", "GSM1513185", "GSM1513186"], "sample_count": 1049, "group_sizes": null, "group_sizes_basis": null, "platform": "9040", "taxon": "Homo sapiens", "title": "miRNA Profiles in patients and controls", "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:GSE21942 not downloaded", "asset:data:geo:GSE21942 licence not read", "asset:data:geo:GSE61741 not downloaded", "asset:data:geo:GSE61741 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}], "targets": [], "gaps": []}, "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": true, "required_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: ppi_network."}, "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": ["GSE21942", "GSE61741"], "resolved_accessions": ["GSE21942", "GSE61741"], "statements": ["In this study, we analyzed the gene expression profiles (GSE21942) and miRNA expression profiles (GSE61741) of MS patient samples that were downloaded from the GEO database and identified differentially expressed mRNAs and miRNAs (DEmRNAs, DEmiRNAs)."], "basis": "The paper names GSE21942, GSE61741 in GEO database and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "assets": ["source:pmid:35273684", "data:geo:GSE21942"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE21942"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:37:17Z", "independence": "single_reader"}, "evidence_check": {"method": null, "availability": null}, "calls": 5, "usage": {"prompt_tokens": 2003, "completion_tokens": 789, "cached_tokens": 128}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:35273684", "type": "paper", "label": "pmid:35273684"}, {"id": "source:pmid:35273684", "type": "manuscript", "label": "PMID 35273684 full text"}, {"id": "data:geo:GSE21942", "type": "dataset", "label": "GEO GSE21942"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35273684", "type": "paper", "label": "pmid:35273684"}, {"id": "source:pmid:35273684", "type": "manuscript", "label": "PMID 35273684 full text"}, {"id": "data:geo:GSE21942", "type": "dataset", "label": "GEO GSE21942"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35273684", "type": "extraction", "used": ["source:pmid:35273684"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE21942", "type": "accession_resolution", "used": ["data:geo:GSE21942"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:35273684", "parent_hash": "sha256:c57419f1d56c83aa20c92424e67a6dac0e83ddad8d13e0b4eb39605ff975623f", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE21942 licence not read", "asset:data:geo:GSE21942 not downloaded", "asset:data:geo:GSE61741 licence not read", "asset:data:geo:GSE61741 not downloaded", "doi", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "network_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["protein-protein interaction"], "order_basis": "analysis_only", "id": "assay:1"}]}