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pmid:30683112

Potential biomarkers of acute myocardial infarction based on weighted gene co-expression network analysis.

Zhihua Liu · Chenguang Ma · Junhua Gu · Ming Yu

Biomedical engineering online · 2019 doi:10.1186/s12938-019-0625-6

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complete

Experiment

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Data

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Analysis

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title
Potential biomarkers of acute myocardial infarction based on weighted gene co-expression network analysis.
doi
10.1186/s12938-019-0625-6
pmid
30683112
authors array · 4 items
[0]
Zhihua Liu
[1]
Chenguang Ma
[2]
Junhua Gu
[3]
Ming Yu
journal
Biomedical engineering online
year
2019
abstract
BACKGROUND: Acute myocardial infarction (AMI) is the common cause of mortality in developed countries. The feasibility of whole-genome gene expression analysis to identify outcome-related genes and dysregulated pathways remains unknown. Molecular marker such as BNP, CRP and other serum inflammatory markers have got the notice at this point. However, these biomarkers exhibit elevated levels in patients with thyroid disease, renal failure and congestive heart failure. In this study, three groups of microarray data sets (GES66360, GSE48060, GSE29532) were collected from GEO, a total of 99, 52 and 55 samples, respectively. Weighted gene co-expression network analysis (WGCNA) was performed to obtain a classifier which composed of related genes that best characterize the AMI. RESULTS: Here, this study obtained three groups of microarray data sets (GES66360, GSE48060, GSE29532) on AMI blood samples, a total of 99, 52 and 24 samples, respectively. In all, 4672 genes, 3185 genes, 3660 genes were identified in GSE66360, GSE48060, GSE60993 modules, respectively. We preformed WGCNA, GO and KEGG pathway enrichment analysis on these three data sets, finding function enrichment of the differential expression gene on inflammation and immune response. Transcriptome analysis were performed in AMI patients at four time points compared to CAD patients with no history of MI, to determine gene expression profiles and their possible changes during the recovery from myocardial infarction. CONCLUSIONS: The results suggested that three overlapping genes (FGFBP2, GFOD1 and MLC1) between two modules could be a potential use of gene biomarkers for the diagnose of AMI.
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All data generated or analyzed during this study are included in this published article.
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Exon-array profiling of peripheral blood cells in the first hours of acute coronary syndrome patients
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Transcriptome from circulating cells suggests dysregulated pathways associated with long-term recurrent events following first-time myocardial infarction.
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GSM1620790
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GSM1620791
[423]
GSM1620792
[424]
GSM1620793
[425]
GSM1620794
[426]
GSM1620795
[427]
GSM1620796
[428]
GSM1620797
[429]
GSM1620798
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GSM1620799
[431]
GSM1620800
[432]
GSM1620801
[433]
GSM1620802
[434]
GSM1620803
[435]
GSM1620804
sample_count
436
group_sizes
null
group_sizes_basis
null
platform
6244
taxon
Homo sapiens
title
Gene expression profiling reveals potential prognostic biomarkers associated with the progression of heart failure
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:GSE60993
role
raw
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geo-series
media_type
application/vnd.ncbi.geo-series+json
uri
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60993
sha256
null
bytes
null
access
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resolved
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null
reader_status
reader_required
identifier
GSE60993
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null
note
All data generated or analyzed during this study are included in this published article.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
All data generated or analyzed during this study are included in this published article.
access_statement_kind
data_availability_statement
sample_accessions array · 33 items
[0]
GSM1495313
[1]
GSM1495314
[2]
GSM1495315
[3]
GSM1495316
[4]
GSM1495317
[5]
GSM1495318
[6]
GSM1495319
[7]
GSM1495320
[8]
GSM1495321
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GSM1495322
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GSM1495323
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GSM1495324
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GSM1495325
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[19]
GSM1495332
[20]
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[21]
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[22]
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[23]
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[24]
GSM1495337
[25]
GSM1495338
[26]
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[27]
GSM1495340
[28]
GSM1495341
[29]
GSM1495342
[30]
GSM1495343
[31]
GSM1495344
[32]
GSM1495345
sample_count
33
group_sizes
null
group_sizes_basis
null
platform
6884
taxon
Homo sapiens
title
Assessment and Diagnostic Relevance of Novel Serum Biomarkers for Early Decision of ST-elevation Myocardial Infarction
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[5] object · 15 fields
id
data:geo:GSE62646
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raw
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geo-series
media_type
application/vnd.ncbi.geo-series+json
uri
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62646
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null
bytes
null
access
open
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null
reader_status
reader_required
identifier
GSE62646
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null
note
All data generated or analyzed during this study are included in this published article.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
All data generated or analyzed during this study are included in this published article.
access_statement_kind
data_availability_statement
sample_accessions array · 98 items
[0]
GSM1530765
[1]
GSM1530766
[2]
GSM1530767
[3]
GSM1530768
[4]
GSM1530769
[5]
GSM1530770
[6]
GSM1530771
[7]
GSM1530772
[8]
GSM1530773
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GSM1530774
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GSM1530775
[11]
GSM1530776
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GSM1530777
[13]
GSM1530778
[14]
GSM1530779
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[16]
GSM1530781
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GSM1530782
[18]
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[19]
GSM1530784
[20]
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[21]
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[22]
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[23]
GSM1530788
[24]
GSM1530789
[25]
GSM1530790
[26]
GSM1530791
[27]
GSM1530792
[28]
GSM1530793
[29]
GSM1530794
[30]
GSM1530795
[31]
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[32]
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[33]
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[34]
GSM1530799
[35]
GSM1530800
[36]
GSM1530801
[37]
GSM1530802
[38]
GSM1530803
[39]
GSM1530804
[40]
GSM1530805
[41]
GSM1530806
[42]
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[43]
GSM1530808
[44]
GSM1530809
[45]
GSM1530810
[46]
GSM1530811
[47]
GSM1530812
[48]
GSM1530813
[49]
GSM1530814
[50]
GSM1530815
[51]
GSM1530816
[52]
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[53]
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[54]
GSM1530819
[55]
GSM1530820
[56]
GSM1530821
[57]
GSM1530822
[58]
GSM1530823
[59]
GSM1530824
[60]
GSM1530825
[61]
GSM1530826
[62]
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[63]
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[64]
GSM1530829
[65]
GSM1530830
[66]
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[67]
GSM1530832
[68]
GSM1530833
[69]
GSM1530834
[70]
GSM1530835
[71]
GSM1530836
[72]
GSM1530837
[73]
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[74]
GSM1530839
[75]
GSM1530840
[76]
GSM1530841
[77]
GSM1530842
[78]
GSM1530843
[79]
GSM1530844
[80]
GSM1530845
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[82]
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[83]
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[85]
GSM1530850
[86]
GSM1530851
[87]
GSM1530852
[88]
GSM1530853
[89]
GSM1530854
[90]
GSM1530855
[91]
GSM1530856
[92]
GSM1530857
[93]
GSM1530858
[94]
GSM1530859
[95]
GSM1530860
[96]
GSM1530861
[97]
GSM1530862
sample_count
98
group_sizes
null
group_sizes_basis
null
platform
6244
taxon
Homo sapiens
title
Altered gene expression pattern in peripheral blood mononuclear cells in patients with acute myocardial infarction
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[6] object · 15 fields
id
data:geo:GSE66360
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=GSE66360
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE66360
version
null
note
All data generated or analyzed during this study are included in this published article.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
All data generated or analyzed during this study are included in this published article.
access_statement_kind
data_availability_statement
sample_accessions array · 99 items
[0]
GSM1620819
[1]
GSM1620820
[2]
GSM1620821
[3]
GSM1620822
[4]
GSM1620823
[5]
GSM1620824
[6]
GSM1620825
[7]
GSM1620826
[8]
GSM1620827
[9]
GSM1620828
[10]
GSM1620829
[11]
GSM1620830
[12]
GSM1620831
[13]
GSM1620832
[14]
GSM1620833
[15]
GSM1620834
[16]
GSM1620835
[17]
GSM1620836
[18]
GSM1620837
[19]
GSM1620838
[20]
GSM1620839
[21]
GSM1620840
[22]
GSM1620841
[23]
GSM1620842
[24]
GSM1620843
[25]
GSM1620844
[26]
GSM1620845
[27]
GSM1620846
[28]
GSM1620847
[29]
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[30]
GSM1620849
[31]
GSM1620850
[32]
GSM1620851
[33]
GSM1620852
[34]
GSM1620853
[35]
GSM1620854
[36]
GSM1620855
[37]
GSM1620856
[38]
GSM1620857
[39]
GSM1620858
[40]
GSM1620859
[41]
GSM1620860
[42]
GSM1620861
[43]
GSM1620862
[44]
GSM1620863
[45]
GSM1620864
[46]
GSM1620865
[47]
GSM1620866
[48]
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[49]
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[50]
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[51]
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[52]
GSM1620871
[53]
GSM1620872
[54]
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[55]
GSM1620874
[56]
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[57]
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[58]
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[59]
GSM1620878
[60]
GSM1620879
[61]
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[62]
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[63]
GSM1620882
[64]
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[65]
GSM1620884
[66]
GSM1620885
[67]
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[68]
GSM1620887
[69]
GSM1620888
[70]
GSM1620889
[71]
GSM1620890
[72]
GSM1620891
[73]
GSM1620892
[74]
GSM1620893
[75]
GSM1620894
[76]
GSM1620895
[77]
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[78]
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[79]
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[80]
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[81]
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[82]
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[83]
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[84]
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[85]
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[86]
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[87]
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[88]
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[89]
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[90]
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[91]
GSM1620910
[92]
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[93]
GSM1620912
[94]
GSM1620913
[95]
GSM1620914
[96]
GSM1620915
[97]
GSM1620916
[98]
GSM1620917
sample_count
99
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
A Whole Blood Molecular Signature for the Identification of Acute Myocardial Infarction Without Relying Upon Myonecrosis (microarray)
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[7] object · 16 fields
id
asset:table:pmid:30683112:1
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table
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jats-table
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application/vnd.jats.table+json
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null
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sha256:25a9f5d711903eb8965ae1099ce7f8196430ec377a5faad6acea78d167a41885
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verified
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read_table
reader_status
available
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section[8]/table-wrap[1]#Tab1
version
null
note
The pathways involved in three cases
structure object · 5 fields
pmcid
PMC6347746
section_index
8
section_title
Microarray differentially expressed gene between AMI and healthy controls
row_count
16
column_count
3
table object · 8 fields
label
Table 1
caption
The pathways involved in three cases
rows array · 16 items
[0] array · 3 items
[0]
Modules
[1]
Pathways
[2]
Q-value (Q < 0.05)
[1] array · 3 items
[0]
GSE48060
[1]
Natural killer cell mediated cytotoxicity
[2]
1.066849e−07
[2] array · 2 items
[0]
Graft-versus-host disease
[1]
1.956196e−07
[3] array · 2 items
[0]
Allograft rejection
[1]
1.237023e−05
[4] array · 2 items
[0]
Cytokine-cytokine receptor interaction
[1]
1.231519e−04
[5] array · 2 items
[0]
Type I diabetes mellitus
[1]
3.664642e−04
[6] array · 3 items
[0]
GSE60993
[1]
Ribosome
[2]
1.315470e−06
[7] array · 2 items
[0]
Intestinal immune network for IgA production
[1]
8.294981e−05
[8] array · 2 items
[0]
Allograft rejection
[1]
1.018873e−04
[9] array · 2 items
[0]
Hematopoietic cell lineage
[1]
3.178231e−04
[10] array · 2 items
[0]
NF-kappa B signaling pathway
[1]
4.203928e−04
[11] array · 3 items
[0]
GSE66360
[1]
Graft-versus-host disease
[2]
7.291560e−18
[12] array · 2 items
[0]
Natural killer cell mediated cytotoxicity
[1]
1.330539e−15
[13] array · 2 items
[0]
Antigen processing and presentation
[1]
1.330539e−15
[14] array · 2 items
[0]
Cytokine-cytokine receptor interaction
[1]
3.994169e−01
[15] array · 2 items
[0]
Gap junction
[1]
3.994169e−01
locator
section[8]/table-wrap[1]#Tab1
[8] object · 16 fields
id
asset:table:pmid:30683112:2
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table
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jats-table
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application/vnd.jats.table+json
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null
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sha256:e9db56943620910af780e9be38d6f12b682ced0d4af63eb981adb0bdeed38845
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1194
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open
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verified
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read_table
reader_status
available
identifier
section[9]/table-wrap[1]#Tab2
version
null
note
The pathways involved in differentially expressed genes compared with different time points following AMI
structure object · 5 fields
pmcid
PMC6347746
section_index
9
section_title
Gene expression profiling at different time points following AMI
row_count
17
column_count
3
table object · 8 fields
label
Table 2
caption
The pathways involved in differentially expressed genes compared with different time points following AMI
rows array · 17 items
[0] array · 3 items
[0]
[1]
Pathways
[2]
Q-value (Q < 0.05)
[1] array · 3 items
[0]
admission versus control group
[1]
Natural killer cell mediated cytotoxicity
[2]
3.142005e−09
[2] array · 2 items
[0]
Graft-versus-host disease
[1]
5.779472e−07
[3] array · 2 items
[0]
Antigen processing and presentation
[1]
2.997803e−03
[4] array · 2 items
[0]
Cytosolic DNA-sensing pathway
[1]
2.302012e−02
[5] array · 3 items
[0]
discharge versus control group
[1]
Natural killer cell mediated cytotoxicity
[2]
8.154634e−10
[6] array · 2 items
[0]
Graft-versus-host disease
[1]
1.164728e−08
[7] array · 2 items
[0]
Antigen processing and presentation
[1]
1.657503e−04
[8] array · 2 items
[0]
Allograft rejection
[1]
2.438676e−02
[9] array · 3 items
[0]
admission versus 6 months
[1]
Oxidative phosphorylation
[2]
3.841450e−15
[10] array · 2 items
[0]
Huntington’s disease
[1]
1.570003e−12
[11] array · 2 items
[0]
Parkinson’s disease
[1]
2.462576e−12
[12] array · 2 items
[0]
Alzheimer’s disease
[1]
1.076534e−11
[13] array · 3 items
[0]
discharge versus 6 months
[1]
Parkinson’s disease
[2]
4.627948e−16
[14] array · 2 items
[0]
Oxidative phosphorylation
[1]
4.627948e−16
[15] array · 2 items
[0]
Alzheimer’s disease
[1]
9.071314e−15
[16] array · 2 items
[0]
Huntington’s disease
[1]
8.428429e−14
locator
section[9]/table-wrap[1]#Tab2
gaps array · 12 items
[0]
asset:data:geo:GSE29532 not downloaded
[1]
asset:data:geo:GSE29532 licence not read
[2]
asset:data:geo:GSE48060 not downloaded
[3]
asset:data:geo:GSE48060 licence not read
[4]
asset:data:geo:GSE59867 not downloaded
[5]
asset:data:geo:GSE59867 licence not read
[6]
asset:data:geo:GSE60993 not downloaded
[7]
asset:data:geo:GSE60993 licence not read
[8]
asset:data:geo:GSE62646 not downloaded
[9]
asset:data:geo:GSE62646 licence not read
[10]
asset:data:geo:GSE66360 not downloaded
[11]
asset:data:geo:GSE66360 licence not read
analysis object · 4 fields
state
partial
methods array · 2 items
[0] object · 10 fields
id
method-1
family
network_analysis
specific
pathway_enrichment
label
Network / pathway analysis
dsl_operations array · 1 item
[0]
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
pathway enrichment
[1] object · 10 fields
id
method-2
family
null
specific
null
label
Weighted gene co-expression network analysis (WGCNA)
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
reordered
quote
“The microarray expression data sets (GES66360, GSE48060, GSE60993) were downloaded from the GEO database.” “WGCNA was used the scale free topology criterion to construct the gene co-expression network.”
targets array · 0 items
gaps array · 1 item
[0]
method.reader_named_unmapped
capability object · 3 fields
state
complete
requirements array · 1 item
[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
true
required_operations array · 1 item
[0]
pathway_enrich
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: pathway_enrichment.
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 · 6 items
[0]
GSE66360
[1]
GSE48060
[2]
GSE60993
[3]
GSE29532
[4]
GSE59867
[5]
GSE62646
resolved_accessions array · 6 items
[0]
GSE66360
[1]
GSE48060
[2]
GSE60993
[3]
GSE29532
[4]
GSE59867
[5]
GSE62646
statements array · 1 item
[0]
All data generated or analyzed during this study are included in this published article.
basis
The paper names GSE66360, GSE48060, GSE60993, GSE29532, GSE59867, GSE62646 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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these biomarkers exhibit elevated levels in patients with thyroid disease, renal failure and congestiv
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patients at four time points compared to CAD patients with no history of MI, to determine gene expressi
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eart failure. In this study, three groups of microarray data sets (GES66360, GSE48060, GSE29532) wer
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S: Here, this study obtained three groups of microarray data sets (GES66360, GSE48060, GSE29532) on
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analysis (Fig. 5).Fig. 4Expression data from microarray experiments in PBMCs—GSE59867 and GSE62646 a
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30683112", "kind": "science-record", "revision": 6, "content_hash": "sha256:ecd5be205d9255b28ce9cece9cfa133f97ee32f9ab3f190fb4f07263053001c2", "created_at": "2026-11-01T15:40:41Z", "updated_at": "2026-11-01T21:21:56Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Potential biomarkers of acute myocardial infarction based on weighted gene co-expression network analysis.", "doi": "10.1186/s12938-019-0625-6", "pmid": "30683112", "authors": ["Zhihua Liu", "Chenguang Ma", "Junhua Gu", "Ming Yu"], "journal": "Biomedical engineering online", "year": 2019, "abstract": "BACKGROUND: Acute myocardial infarction (AMI) is the common cause of mortality in developed countries. The feasibility of whole-genome gene expression analysis to identify outcome-related genes and dysregulated pathways remains unknown. Molecular marker such as BNP, CRP and other serum inflammatory markers have got the notice at this point. However, these biomarkers exhibit elevated levels in patients with thyroid disease, renal failure and congestive heart failure. In this study, three groups of microarray data sets (GES66360, GSE48060, GSE29532) were collected from GEO, a total of 99, 52 and 55 samples, respectively. Weighted gene co-expression network analysis (WGCNA) was performed to obtain a classifier which composed of related genes that best characterize the AMI.\nRESULTS: Here, this study obtained three groups of microarray data sets (GES66360, GSE48060, GSE29532) on AMI blood samples, a total of 99, 52 and 24 samples, respectively. In all, 4672 genes, 3185 genes, 3660 genes were identified in GSE66360, GSE48060, GSE60993 modules, respectively. We preformed WGCNA, GO and KEGG pathway enrichment analysis on these three data sets, finding function enrichment of the differential expression gene on inflammation and immune response. Transcriptome analysis were performed in AMI patients at four time points compared to CAD patients with no history of MI, to determine gene expression profiles and their possible changes during the recovery from myocardial infarction.\nCONCLUSIONS: The results suggested that three overlapping genes (FGFBP2, GFOD1 and MLC1) between two modules could be a potential use of gene biomarkers for the diagnose of AMI.", "claims": [{"id": "claim-data-access", "statement": "All data generated or analyzed during this study are included in this published article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30683112", "locator": "sections[14] \"ack\" paragraph 1", "quote": "All data generated or analyzed during this study are included in this published article."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:30683112"], "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:GSE29532"], "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:GSE29532"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:30683112", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12938-019-0625-6", "sha256": 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