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pmid:33002344

Screening lncRNAs with diagnostic and prognostic value for human stomach adenocarcinoma based on machine learning and mRNA-lncRNA co-expression network analysis.

Qun Li · Xiaofeng Liu · Jia Gu · Jinming Zhu · Zhi Wei · Hua Huang

Molecular genetics & genomic medicine · 2020 doi:10.1002/mgg3.1512

Paper

complete

Experiment

partial

Data

partial

Analysis

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Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
id
pmid:33002344
kind
science-record
content_hash
sha256:8c95ab77a824cbbbea56af90096df4293e2ea4fa8fb9d31217930044ca5d3dd6
schema
https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T15:41:12Z
updated_at
2026-11-01T22:45:24Z
generator object · 2 fields
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corpus-assay-engine
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reading-sci-2026-11-01
paper object · 10 fields
state
complete
title
Screening lncRNAs with diagnostic and prognostic value for human stomach adenocarcinoma based on machine learning and mRNA-lncRNA co-expression network analysis.
doi
10.1002/mgg3.1512
pmid
33002344
authors array · 6 items
[0]
Qun Li
[1]
Xiaofeng Liu
[2]
Jia Gu
[3]
Jinming Zhu
[4]
Zhi Wei
[5]
Hua Huang
journal
Molecular genetics & genomic medicine
year
2020
abstract
BACKGROUND: Stomach adenocarcinoma (STAD), is one of the most lethal malignancies around the world. The aim of this study was to find the long noncoding RNAs (lncRNAs) acting as diagnostic and prognostic biomarker of STAD. METHODS: Base on TCGA dataset, the differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified between STAD and normal tissue. The machine learning and survival analysis were performed to evaluate the potential diagnostic and prognostic value of lncRNAs for STAD. We also build the co-expression network and functional annotation. The expression of selected candidate mRNAs and lncRNAs were validated by Quantitative real-time polymerase chain reaction (qRT-PCR) and GSE27342 dataset. GSE27342 dataset were also to perform gene set enrichment analysis. RESULTS: A total of 814 DEmRNAs and 106 DElncRNAs between STAD and normal tissue were obtained. FOXD2-AS1, LINC01235, and RP11-598F7.5 were defined as optimal diagnostic lncRNA biomarkers for STAD. The area under curve (AUC) of the decision tree model, random forests model, and support vector machine (SVM) model were 0.797, 0.981, and 0.983, and the specificity and sensitivity of the three model were 75.0% and 97.1%, 96.9% and 96%, and 96.9% and 97.1%, respectively. Among them, LINC01235 was not only an optimal diagnostic lncRNA biomarkers, but also related to survival time. The expression of three DEmRNAs (ESM1, WNT2, and COL10A1) and three optimal diagnostic lncRNAs biomarkers (FOXD2-AS1, RP11-598F7.5, and LINC01235) in qRT-PCR validation was were consistent with our integrated analysis. Except for FOXD2-AS1, ESM1, WNT2, COL10A1, and LINC01235 were upregulated in STAD, which was consistent with our integration results. Gene set enrichment analysis results indicated that DNA replication, Cell cycle, ECM-receptor interaction, and P53 signaling pathway were four significantly enriched pathways in STAD. CONCLUSION: Our study identified three DElncRNAs as potential diagnostic biomarkers of STAD. Among them, LINC01235 also was a prognostic lncRNA biomarkers.
claims array · 1 item
[0] object · 6 fields
id
claim-method
statement
The DElncRNAs and DEmRNAs in STAD compared to adjacent normal tissues were calculated using the R package DESeq2. Benjamini and Hochberg multiple testing method was applied to acquire the false discovery rate (FDR).
kind
methodological
target
null
evidence array · 1 item
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locator
sections[4] "Identification of DEmRNAs and DElncRNAs" paragraph 2
quote
The DElncRNAs and DEmRNAs in STAD compared to adjacent normal tissues were calculated using the R package DESeq2. Benjamini and Hochberg multiple testing method was applied to acquire the false discovery rate (FDR).
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Read the published estimate from the source
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The claim, method and evidence span published with the source article.
parameters object · 0 fields
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[0]
source:pmid:33002344
outputs array · 1 item
[0]
the published estimate and its evidence
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Obtain the source data from the named repository
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The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.
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the source data with its repository provenance
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Run the published analysis
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Apply the paper's statistical method to the resolved series and compare the result with the published target.
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fdr_threshold
with Benjamini–Hochberg false discovery rate correction
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the replicated result and its comparison
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https://doi.org/10.1002/mgg3.1512
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10.1002/mgg3.1512
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Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.
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PMC7667366
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Primer sequences used for qRT‐PCR
structure object · 5 fields
pmcid
PMC7667366
section_index
9
section_title
Confirmation by qRT‐PCR
row_count
15
column_count
2
table object · 8 fields
label
TABLE 1
caption
Primer sequences used for qRT‐PCR
rows array · 15 items
[0] array · 2 items
[0]
Name
[1]
Sequence (5′ to 3′)
[1] array · 2 items
[0]
ACTB‐F
[1]
CATGTACGTTGCTATCCAGGC
[2] array · 2 items
[0]
ACTB‐R
[1]
CTCCTTAATGTCACGCACGAT
[3] array · 2 items
[0]
ESM1‐F
[1]
CAGTGAGTGCAAAAGCAGCC
[4] array · 2 items
[0]
ESM1‐R
[1]
TCCTCCCCATTAGAAGGCTGA
[5] array · 2 items
[0]
WNT2‐F
[1]
TCTCGGTGGAATCTGGCTCTGG
[6] array · 2 items
[0]
WNT2‐R
[1]
TGGCTAATGGCACGCATCACATC
[7] array · 2 items
[0]
COL10A1‐F
[1]
CAGGAAAACCAGGCTACGGA
[8] array · 2 items
[0]
COL10A1‐R
[1]
CCAGCTGGTCCAACZTCTCC
[9] array · 2 items
[0]
FOXD2‐AS1‐F
[1]
TGCATCCTGTGTCCTGTGTC
[10] array · 2 items
[0]
FOXD2‐AS1‐R
[1]
CCACTAGGGTCTCGCTGTTG
[11] array · 2 items
[0]
RP11‐598F7.5‐F
[1]
GCATGTCTGTCTCAAGCTGC
[12] array · 2 items
[0]
RP11‐598F7.5‐R
[1]
TGCAGAAGTTCGTGGAGGAC
[13] array · 2 items
[0]
LINC01235‐F
[1]
CGAGACCAGCCTGACCAACATG
[14] array · 2 items
[0]
LINC01235‐R
[1]
CTCCTGCCTTAGCCTCCTGAGTAG
locator
section[9]/table-wrap[1]#mgg31512-tbl-0001
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DElncRNAs between STAD and normal tissues after reduced dimensions of data by LASSO algorithm
structure object · 5 fields
pmcid
PMC7667366
section_index
14
section_title
Identification of optimal diagnostic lncRNAs biomarkers for STAD
row_count
29
column_count
5
table object · 8 fields
label
TABLE 2
caption
DElncRNAs between STAD and normal tissues after reduced dimensions of data by LASSO algorithm
rows array · 29 items
[0] array · 5 items
[0]
Symbol
[1]
log2FoldChange
[2]
p‐value
[3]
FDR
[4]
Updown
[1] array · 5 items
[0]
FOXD2‐AS1
[1]
2.139327751
[2]
2.28E‐31
[3]
2.63E‐28
[4]
Up
[2] array · 5 items
[0]
IL12A‐AS1
[1]
−3.340180888
[2]
5.18E‐31
[3]
4.78E‐28
[4]
Down
[3] array · 5 items
[0]
AC090616.2
[1]
−2.265896134
[2]
1.14E‐29
[3]
8.77E‐27
[4]
Down
[4] array · 5 items
[0]
RP11‐598F7.5
[1]
2.374331116
[2]
2.37E‐27
[3]
1.37E‐24
[4]
Up
[5] array · 5 items
[0]
ADAMTS9‐AS1
[1]
−2.750538461
[2]
3.62E‐27
[3]
1.86E‐24
[4]
Down
[6] array · 5 items
[0]
DLGAP1‐AS2
[1]
2.043503544
[2]
2.23E‐25
[3]
6.44E‐23
[4]
Up
[7] array · 5 items
[0]
RP11‐613D13.8
[1]
−2.423609575
[2]
2.96E‐24
[3]
7.19E‐22
[4]
Down
[8] array · 5 items
[0]
LINC02158
[1]
−2.245429764
[2]
3.21E‐24
[3]
7.39E‐22
[4]
Down
[9] array · 5 items
[0]
AL928768.3
[1]
−3.703197788
[2]
1.06E‐22
[3]
1.96E‐20
[4]
Down
[10] array · 5 items
[0]
LINC01235
[1]
2.53991133
[2]
5.63E‐22
[3]
8.95E‐20
[4]
Up
[11] array · 5 items
[0]
LINC01336
[1]
−2.549764194
[2]
5.00E‐20
[3]
5.12E‐18
[4]
Down
[12] array · 5 items
[0]
AC015849.16
[1]
2.256425866
[2]
9.54E‐20
[3]
9.36E‐18
[4]
Up
[13] array · 5 items
[0]
RNF144A‐AS1
[1]
2.139212352
[2]
7.70E‐19
[3]
6.96E‐17
[4]
Up
[14] array · 5 items
[0]
C5orf66‐AS1
[1]
−3.187219896
[2]
9.81E‐19
[3]
8.53E‐17
[4]
Down
[15] array · 5 items
[0]
CDKN2B‐AS1
[1]
−2.587107347
[2]
2.91E‐18
[3]
2.27E‐16
[4]
Down
[16] array · 5 items
[0]
LINC01697
[1]
−2.747733567
[2]
9.67E‐18
[3]
6.73E‐16
[4]
Down
[17] array · 5 items
[0]
AC073283.7
[1]
2.081655386
[2]
2.20E‐16
[3]
1.18E‐14
[4]
Up
[18] array · 5 items
[0]
LINC00982
[1]
−2.306850193
[2]
1.49E‐15
[3]
6.46E‐14
[4]
Down
[19] array · 5 items
[0]
RP11‐963H4.3
[1]
−2.022400723
[2]
7.67E‐15
[3]
3.00E‐13
[4]
Down
[20] array · 5 items
[0]
RP11‐641D5.2
[1]
−2.040949727
[2]
1.08E‐14
[3]
3.99E‐13
[4]
Down
[21] array · 5 items
[0]
PGM5‐AS1
[1]
−3.192676148
[2]
1.26E‐14
[3]
4.58E‐13
[4]
Down
[22] array · 5 items
[0]
RP11‐7 K24.3
[1]
−2.041496455
[2]
9.89E‐14
[3]
2.90E‐12
[4]
Down
[23] array · 5 items
[0]
AC096579.15
[1]
−2.46634156
[2]
1.27E‐13
[3]
3.67E‐12
[4]
Down
[24] array · 5 items
[0]
AC104024.1
[1]
−2.111937683
[2]
1.75E‐13
[3]
4.82E‐12
[4]
Down
[25] array · 5 items
[0]
PART1
[1]
−2.31587256
[2]
8.27E‐12
[3]
1.64E‐10
[4]
Down
[26] array · 5 items
[0]
C20orf166‐AS1
[1]
−2.491364692
[2]
2.57E‐11
[3]
4.40E‐10
[4]
Down
[27] array · 5 items
[0]
CASC9
[1]
2.276494335
[2]
2.79E‐11
[3]
4.69E‐10
[4]
Up
[28] array · 5 items
[0]
AF001548.6
[1]
−2.081376039
[2]
1.45E‐08
[3]
1.29E‐07
[4]
Down
locator
section[14]/table-wrap[1]#mgg31512-tbl-0002
[3] object · 16 fields
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asset:table:pmid:33002344:3
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format
jats-table
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application/vnd.jats.table+json
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sha256
sha256:aa1d51239eaefe30068f84d8b2d5b0a1c655d011984531464ea88e3d8a5c7554
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note
DElncRNAs between STAD and normal tissues after reduced dimensions of data by Elastic net
structure object · 5 fields
pmcid
PMC7667366
section_index
14
section_title
Identification of optimal diagnostic lncRNAs biomarkers for STAD
row_count
50
column_count
5
table object · 8 fields
label
TABLE 3
caption
DElncRNAs between STAD and normal tissues after reduced dimensions of data by Elastic net
rows array · 50 items
[0] array · 5 items
[0]
Symbol
[1]
log2FoldChange
[2]
p‐value
[3]
FDR
[4]
Updown
[1] array · 5 items
[0]
FOXD2‐AS1
[1]
2.139328
[2]
2.28E‐31
[3]
2.63E‐28
[4]
Up
[2] array · 5 items
[0]
RP11‐598F7.5
[1]
2.374331
[2]
2.37E‐27
[3]
1.37E‐24
[4]
Up
[3] array · 5 items
[0]
LINC01235
[1]
2.539911
[2]
5.63E‐22
[3]
8.95E‐20
[4]
Up
[4] array · 5 items
[0]
AL928768.3
[1]
−3.7032
[2]
1.06E‐22
[3]
1.96E‐20
[4]
Down
[5] array · 5 items
[0]
GAPLINC
[1]
2.062859
[2]
1.75E‐18
[3]
1.43E‐16
[4]
Up
[6] array · 5 items
[0]
DUXAP8
[1]
3.316478
[2]
1.22E‐35
[3]
2.80E‐32
[4]
Up
[7] array · 5 items
[0]
LINC01336
[1]
−2.54976
[2]
5.00E‐20
[3]
5.12E‐18
[4]
Down
[8] array · 5 items
[0]
DLGAP1‐AS2
[1]
2.043504
[2]
2.23E‐25
[3]
6.44E‐23
[4]
Up
[9] array · 5 items
[0]
LINC01697
[1]
−2.74773
[2]
9.67E‐18
[3]
6.73E‐16
[4]
Down
[10] array · 5 items
[0]
C5orf66‐AS1
[1]
−3.18722
[2]
9.81E‐19
[3]
8.53E‐17
[4]
Down
[11] array · 5 items
[0]
RP1‐60O19.1
[1]
2.739187
[2]
4.28E‐14
[3]
1.32E‐12
[4]
Up
[12] array · 5 items
[0]
RP11‐867G23.10
[1]
−3.08974
[2]
1.47E‐25
[3]
4.53E‐23
[4]
Down
[13] array · 5 items
[0]
ADAMTS9‐AS2
[1]
−2.15844
[2]
4.67E‐16
[3]
2.24E‐14
[4]
Down
[14] array · 5 items
[0]
AC015849.16
[1]
2.256426
[2]
9.54E‐20
[3]
9.36E‐18
[4]
Up
[15] array · 5 items
[0]
RNF144A‐AS1
[1]
2.139212
[2]
7.70E‐19
[3]
6.96E‐17
[4]
Up
[16] array · 5 items
[0]
LINC02086
[1]
2.525563
[2]
2.62E‐14
[3]
8.68E‐13
[4]
Up
[17] array · 5 items
[0]
KRT7‐AS
[1]
2.226896
[2]
3.66E‐12
[3]
8.11E‐11
[4]
Up
[18] array · 5 items
[0]
AC073283.7
[1]
2.081655
[2]
2.20E‐16
[3]
1.18E‐14
[4]
Up
[19] array · 5 items
[0]
LINC02158
[1]
−2.24543
[2]
3.21E‐24
[3]
7.39E‐22
[4]
Down
[20] array · 5 items
[0]
RP11‐770 J1.3
[1]
−2.05015
[2]
1.84E‐39
[3]
8.50E‐36
[4]
Down
[21] array · 5 items
[0]
PGM5‐AS1
[1]
−3.19268
[2]
1.26E‐14
[3]
4.58E‐13
[4]
Down
[22] array · 5 items
[0]
MEF2C‐AS1
[1]
−2.09002
[2]
3.43E‐16
[3]
1.76E‐14
[4]
Down
[23] array · 5 items
[0]
RBMS3‐AS3
[1]
−2.2516
[2]
2.02E‐15
[3]
8.47E‐14
[4]
Down
[24] array · 5 items
[0]
RP11‐211G23.2
[1]
2.118864
[2]
2.16E‐12
[3]
5.14E‐11
[4]
Up
[25] array · 5 items
[0]
CTD‐2540F13.2
[1]
2.141602
[2]
9.78E‐18
[3]
6.73E‐16
[4]
Up
[26] array · 5 items
[0]
AC108676.1
[1]
2.441715
[2]
4.71E‐16
[3]
2.24E‐14
[4]
Up
[27] array · 5 items
[0]
CASC9
[1]
2.276494
[2]
2.79E‐11
[3]
4.69E‐10
[4]
Up
[28] array · 5 items
[0]
PART1
[1]
−2.31587
[2]
8.27E‐12
[3]
1.64E‐10
[4]
Down
[29] array · 5 items
[0]
TRPM2‐AS
[1]
2.748372
[2]
2.12E‐20
[3]
2.39E‐18
[4]
Up
[30] array · 5 items
[0]
CTD‐2540F13.2
[1]
2.141602
[2]
9.78E‐18
[3]
6.73E‐16
[4]
Up
[31] array · 5 items
[0]
RP11‐21A7A.2
[1]
−2.52023
[2]
9.31E‐17
[3]
5.43E‐15
[4]
Down
[32] array · 5 items
[0]
IL12A‐AS1
[1]
−3.34018
[2]
5.18E‐31
[3]
4.78E‐28
[4]
Down
[33] array · 5 items
[0]
AC096579.15
[1]
−2.46634
[2]
1.27E‐13
[3]
3.67E‐12
[4]
Down
[34] array · 5 items
[0]
RP11‐641D5.2
[1]
−2.04095
[2]
1.08E‐14
[3]
3.99E‐13
[4]
Down
[35] array · 5 items
[0]
RP11‐963H4.3
[1]
−2.0224
[2]
7.67E‐15
[3]
3.00E‐13
[4]
Down
[36] array · 5 items
[0]
CDKN2B‐AS1
[1]
−2.58711
[2]
2.91E‐18
[3]
2.27E‐16
[4]
Down
[37] array · 5 items
[0]
RP11‐613D13.8
[1]
−2.42361
[2]
2.96E‐24
[3]
7.19E‐22
[4]
Down
[38] array · 5 items
[0]
RP11‐626H12.2
[1]
2.19915
[2]
3.16E‐17
[3]
1.94E‐15
[4]
Up
[39] array · 5 items
[0]
AC090616.2
[1]
−2.2659
[2]
1.14E‐29
[3]
8.77E‐27
[4]
Down
[40] array · 5 items
[0]
C20orf166‐AS1
[1]
−2.49136
[2]
2.57E‐11
[3]
4.40E‐10
[4]
Down
[41] array · 5 items
[0]
UBXN10‐AS1
[1]
−2.77015
[2]
6.71E‐20
[3]
6.73E‐18
[4]
Down
[42] array · 5 items
[0]
LINC00671
[1]
−2.66457
[2]
3.07E‐20
[3]
3.29E‐18
[4]
Down
[43] array · 5 items
[0]
LINC00982
[1]
−2.30685
[2]
1.49E‐15
[3]
6.46E‐14
[4]
Down
[44] array · 5 items
[0]
AC104024.1
[1]
−2.11194
[2]
1.75E‐13
[3]
4.82E‐12
[4]
Down
[45] array · 5 items
[0]
SOX21‐AS1
[1]
−2.18199
[2]
2.01E‐07
[3]
1.34E‐06
[4]
Down
[46] array · 5 items
[0]
RP11‐351 J23.1
[1]
−2.7255
[2]
5.24E‐14
[3]
1.61E‐12
[4]
Down
[47] array · 5 items
[0]
AF001548.6
[1]
−2.08138
[2]
1.45E‐08
[3]
1.29E‐07
[4]
Down
[48] array · 5 items
[0]
RP11‐7 K24.3
[1]
−2.0415
[2]
9.89E‐14
[3]
2.90E‐12
[4]
Down
[49] array · 5 items
[0]
RP11‐800A18.4
[1]
−2.53106
[2]
1.73E‐12
[3]
4.18E‐11
[4]
Down
locator
section[14]/table-wrap[2]#mgg31512-tbl-0003
[4] object · 16 fields
id
asset:table:pmid:33002344:4
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:2e34c00e3935e9e407567b8b6950e01cf8c081475cdda31d34d9d045a226ca48
bytes
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access
open
state
verified
reader
read_table
reader_status
available
identifier
section[9]/table-wrap[1]#mgg31512-tbl-0001
version
null
note
Primer sequences used for qRT‐PCR
structure object · 5 fields
pmcid
PMC7667366
section_index
18
section_title
Confirmation by qRT‐PCR
row_count
15
column_count
2
table object · 8 fields
label
TABLE 1
caption
Primer sequences used for qRT‐PCR
rows array · 15 items
[0] array · 2 items
[0]
Name
[1]
Sequence (5′ to 3′)
[1] array · 2 items
[0]
ACTB‐F
[1]
CATGTACGTTGCTATCCAGGC
[2] array · 2 items
[0]
ACTB‐R
[1]
CTCCTTAATGTCACGCACGAT
[3] array · 2 items
[0]
ESM1‐F
[1]
CAGTGAGTGCAAAAGCAGCC
[4] array · 2 items
[0]
ESM1‐R
[1]
TCCTCCCCATTAGAAGGCTGA
[5] array · 2 items
[0]
WNT2‐F
[1]
TCTCGGTGGAATCTGGCTCTGG
[6] array · 2 items
[0]
WNT2‐R
[1]
TGGCTAATGGCACGCATCACATC
[7] array · 2 items
[0]
COL10A1‐F
[1]
CAGGAAAACCAGGCTACGGA
[8] array · 2 items
[0]
COL10A1‐R
[1]
CCAGCTGGTCCAACZTCTCC
[9] array · 2 items
[0]
FOXD2‐AS1‐F
[1]
TGCATCCTGTGTCCTGTGTC
[10] array · 2 items
[0]
FOXD2‐AS1‐R
[1]
CCACTAGGGTCTCGCTGTTG
[11] array · 2 items
[0]
RP11‐598F7.5‐F
[1]
GCATGTCTGTCTCAAGCTGC
[12] array · 2 items
[0]
RP11‐598F7.5‐R
[1]
TGCAGAAGTTCGTGGAGGAC
[13] array · 2 items
[0]
LINC01235‐F
[1]
CGAGACCAGCCTGACCAACATG
[14] array · 2 items
[0]
LINC01235‐R
[1]
CTCCTGCCTTAGCCTCCTGAGTAG
locator
section[9]/table-wrap[1]#mgg31512-tbl-0001
gaps array · 0 items
analysis object · 4 fields
state
complete
methods array · 3 items
[0] object · 10 fields
id
method-1
family
differential_expression
specific
deseq2
label
Differential expression analysis
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
parameters object · 1 field
fdr_threshold
with Benjamini–Hochberg false discovery rate correction
data_shapes array · 1 item
[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
band
verbatim
quote
The DElncRNAs and DEmRNAs in STAD compared to adjacent normal tissues were calculated using the R package DESeq2. Benjamini and Hochberg multiple testing method was applied to acquire the false discovery rate (FDR).
[1] object · 10 fields
id
method-2
family
machine_learning
specific
support_vector_machine
label
Machine learning
dsl_operations array · 3 items
[0]
train_classifier
[1]
cross_validate
[2]
roc_auc
missing_operations array · 0 items
parameters object · 1 field
auc
The area under curve (AUC) of the decision tree m
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.7
band
medium
quote
support vector machine
[2] object · 10 fields
id
method-3
family
machine_learning
specific
decision_tree
label
Machine learning
dsl_operations array · 3 items
[0]
train_classifier
[1]
cross_validate
[2]
roc_auc
missing_operations array · 0 items
parameters object · 1 field
auc
The area under curve (AUC) of the decision tree m
data_shapes array · 1 item
[0]
labelled_feature_matrix
evidence object · 3 fields
score
0.7
band
medium
quote
decision tree
targets array · 0 items
gaps array · 0 items
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
blocked
tier
R4
blocked_on
data:accession_absent
axes object · 3 fields
method object · 5 fields
tier
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expressible
true
required_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
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: deseq2.
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
R4
reachable
false
accessions array · 0 items
resolved_accessions array · 0 items
statements array · 0 items
basis
The paper names no accession to its source data, so the data has to come from the authors.
can_run object · 3 fields
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
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fdr_bh
assets array · 5 items
[0]
source:pmid:33002344
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asset:table:pmid:33002344:1
[2]
asset:table:pmid:33002344:2
[3]
asset:table:pmid:33002344:3
[4]
asset:table:pmid:33002344:4
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:None
gaps array · 1 item
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data:accession_absent
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T19:12:07Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
3
usage object · 3 fields
prompt_tokens
32097
completion_tokens
1872
cached_tokens
792
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
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review.independent_reader
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review.machine_critique
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review.human_critique
execution object · 5 fields
state
absent
status
not_run
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null
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gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:33002344
type
paper
label
pmid:33002344
[1] object · 3 fields
id
source:pmid:33002344
type
manuscript
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PMID 33002344 full text
[2] object · 3 fields
id
data:geo:None
type
dataset
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GEO None
activities array · 3 items
[0] object · 4 fields
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activity-reading-sci-2026-11-01
type
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pmid:33002344
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pmid:33002344
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source:pmid:33002344
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PMID 33002344 full text
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data:geo:None
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GEO None
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agent:corpus-assay-engine
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id
activity-read-33002344
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source:pmid:33002344
agent
agent:minimax-reader
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accession_resolution
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data:geo:None
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agent:corpus-assay-engine
agents array · 2 items
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id
agent:corpus-assay-engine
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id
agent:minimax-reader
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MiniMax literature reader
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dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
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lineage object · 4 fields
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pmid:33002344
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assays array · 1 item
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role
analysis
definition_id
differential_expression
definition_version
f2132e96ae6c7a4e
required_operations array · 3 items
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normalise_counts
[1]
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fdr_bh
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
The DElncRNAs and DEmRNAs in STAD compared to adjacent normal tissues were calculated using the R package DESeq2. Benjamini and Hochberg multiple testing method was applied to acquire the false discovery rate (FDR).
order_basis
analysis_only
id
assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33002344", "kind": "science-record", "revision": 8, "content_hash": "sha256:8c95ab77a824cbbbea56af90096df4293e2ea4fa8fb9d31217930044ca5d3dd6", "created_at": "2026-11-01T15:41:12Z", "updated_at": "2026-11-01T22:45:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Screening lncRNAs with diagnostic and prognostic value for human stomach adenocarcinoma based on machine learning and mRNA-lncRNA co-expression network analysis.", "doi": "10.1002/mgg3.1512", "pmid": "33002344", "authors": ["Qun Li", "Xiaofeng Liu", "Jia Gu", "Jinming Zhu", "Zhi Wei", "Hua Huang"], "journal": "Molecular genetics & genomic medicine", "year": 2020, "abstract": "BACKGROUND: Stomach adenocarcinoma (STAD), is one of the most lethal malignancies around the world. The aim of this study was to find the long noncoding RNAs (lncRNAs) acting as diagnostic and prognostic biomarker of STAD.\nMETHODS: Base on TCGA dataset, the differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified between STAD and normal tissue. The machine learning and survival analysis were performed to evaluate the potential diagnostic and prognostic value of lncRNAs for STAD. We also build the co-expression network and functional annotation. The expression of selected candidate mRNAs and lncRNAs were validated by Quantitative real-time polymerase chain reaction (qRT-PCR) and GSE27342 dataset. GSE27342 dataset were also to perform gene set enrichment analysis.\nRESULTS: A total of 814 DEmRNAs and 106 DElncRNAs between STAD and normal tissue were obtained. FOXD2-AS1, LINC01235, and RP11-598F7.5 were defined as optimal diagnostic lncRNA biomarkers for STAD. The area under curve (AUC) of the decision tree model, random forests model, and support vector machine (SVM) model were 0.797, 0.981, and 0.983, and the specificity and sensitivity of the three model were 75.0% and 97.1%, 96.9% and 96%, and 96.9% and 97.1%, respectively. Among them, LINC01235 was not only an optimal diagnostic lncRNA biomarkers, but also related to survival time. The expression of three DEmRNAs (ESM1, WNT2, and COL10A1) and three optimal diagnostic lncRNAs biomarkers (FOXD2-AS1, RP11-598F7.5, and LINC01235) in qRT-PCR validation was were consistent with our integrated analysis. Except for FOXD2-AS1, ESM1, WNT2, COL10A1, and LINC01235 were upregulated in STAD, which was consistent with our integration results. Gene set enrichment analysis results indicated that DNA replication, Cell cycle, ECM-receptor interaction, and P53 signaling pathway were four significantly enriched pathways in STAD.\nCONCLUSION: Our study identified three DElncRNAs as potential diagnostic biomarkers of STAD. Among them, LINC01235 also was a prognostic lncRNA biomarkers.", "claims": [{"id": "claim-method", "statement": "The DElncRNAs and DEmRNAs in STAD compared to adjacent normal tissues were calculated using the R package DESeq2. Benjamini and Hochberg multiple testing method was applied to acquire the false discovery rate (FDR).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33002344", "locator": "sections[4] \"Identification of DEmRNAs and DElncRNAs\" paragraph 2", "quote": "The DElncRNAs and DEmRNAs in STAD compared to adjacent normal tissues were calculated using the R package DESeq2. Benjamini and Hochberg multiple testing method was applied to acquire the false discovery rate (FDR)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "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:33002344"], "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": "blocked", "blocked_on": "data:accession_absent", "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": [], "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": {"fdr_threshold": "with Benjamini–Hochberg false discovery rate correction"}, "inputs": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33002344", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": 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"structure": {"pmcid": "PMC7667366", "section_index": 9, "section_title": "Confirmation by qRT‐PCR", "row_count": 15, "column_count": 2}, "table": {"label": "TABLE 1", "caption": "Primer sequences used for qRT‐PCR", "rows": [["Name", "Sequence (5′ to 3′)"], ["ACTB‐F", "CATGTACGTTGCTATCCAGGC"], ["ACTB‐R", "CTCCTTAATGTCACGCACGAT"], ["ESM1‐F", "CAGTGAGTGCAAAAGCAGCC"], ["ESM1‐R", "TCCTCCCCATTAGAAGGCTGA"], ["WNT2‐F", "TCTCGGTGGAATCTGGCTCTGG"], ["WNT2‐R", "TGGCTAATGGCACGCATCACATC"], ["COL10A1‐F", "CAGGAAAACCAGGCTACGGA"], ["COL10A1‐R", "CCAGCTGGTCCAACZTCTCC"], ["FOXD2‐AS1‐F", "TGCATCCTGTGTCCTGTGTC"], ["FOXD2‐AS1‐R", "CCACTAGGGTCTCGCTGTTG"], ["RP11‐598F7.5‐F", "GCATGTCTGTCTCAAGCTGC"], ["RP11‐598F7.5‐R", "TGCAGAAGTTCGTGGAGGAC"], ["LINC01235‐F", "CGAGACCAGCCTGACCAACATG"], ["LINC01235‐R", "CTCCTGCCTTAGCCTCCTGAGTAG"]], "row_count": 15, "column_count": 2, "numeric_cells": 7, "header_rows": 1, "locator": "section[9]/table-wrap[1]#mgg31512-tbl-0001"}}, {"id": "asset:table:pmid:33002344:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:017b5c33fe9194d4033ed5ac27aa0e5c893d017297c26d3cdda7f6e1ab3cd032", "bytes": 2118, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[14]/table-wrap[1]#mgg31512-tbl-0002", "version": null, "note": "DElncRNAs between STAD and normal tissues after reduced dimensions of data by LASSO algorithm", "structure": {"pmcid": "PMC7667366", "section_index": 14, "section_title": "Identification of optimal diagnostic lncRNAs biomarkers for STAD", "row_count": 29, "column_count": 5}, "table": {"label": "TABLE 2", "caption": "DElncRNAs between STAD and normal tissues after reduced dimensions of data by LASSO algorithm", "rows": [["Symbol", "log2FoldChange", "p‐value", "FDR", "Updown"], ["FOXD2‐AS1", "2.139327751", "2.28E‐31", "2.63E‐28", "Up"], ["IL12A‐AS1", "−3.340180888", "5.18E‐31", "4.78E‐28", "Down"], ["AC090616.2", 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