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pmid:31428132

Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis.

Jun-Li Deng · Yun-Hua Xu · Guo Wang

Frontiers in genetics · 2019 doi:10.3389/fgene.2019.00695

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complete

Experiment

complete

Data

partial

Analysis

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title
Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis.
doi
10.3389/fgene.2019.00695
pmid
31428132
authors array · 3 items
[0]
Jun-Li Deng
[1]
Yun-Hua Xu
[2]
Guo Wang
journal
Frontiers in genetics
year
2019
abstract
Background: The molecular mechanism of tumorigenesis remains to be fully understood in breast cancer. It is urgently required to identify genes that are associated with breast cancer development and prognosis and to elucidate the underlying molecular mechanisms. In the present study, we aimed to identify potential pathogenic and prognostic differentially expressed genes (DEGs) in breast adenocarcinoma through bioinformatic analysis of public datasets. Methods: Four datasets (GSE21422, GSE29431, GSE42568, and GSE61304) from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) dataset were used for the bioinformatic analysis. DEGs were identified using LIMMA Package of R. The GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses were conducted through FunRich. The protein-protein interaction (PPI) network of the DEGs was established through STRING (Search Tool for the Retrieval of Interacting Genes database) website, visualized by Cytoscape and further analyzed by Molecular Complex Detection (MCODE). UALCAN and Kaplan-Meier (KM) plotter were employed to analyze the expression levels and prognostic values of hub genes. The expression levels of the hub genes were also validated in clinical samples from breast cancer patients. In addition, the gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD). Results: In total, 203 up-regulated and 118 down-regulated DEGs were identified. Mitotic cell cycle and epithelial-to-mesenchymal transition pathway were the major enriched pathways for the up-regulated and down-regulated genes, respectively. The PPI network was constructed with 314 nodes and 1,810 interactions, and two significant modules are selected. The most significant enriched pathway in module 1 was the mitotic cell cycle. Moreover, six hub genes were selected and validated in clinical sample for further analysis owing to the high degree of connectivity, including CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK, and they were all correlated to worse overall survival (OS) in breast cancer. Conclusion: These results revealed that mitotic cell cycle and epithelial-to-mesenchymal transition pathway could be potential pathways accounting for the progression in breast cancer, and CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK may be potential crucial genes. Further, it could be utilized as new biomarkers for prognosis and potential new targets for drug synthesis of breast cancer.
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Identification of DEGs was performed using the LIMMA package of R (Diboun et al., 2006).
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sections[5] "Identification of DEGs" paragraph 2
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Identification of DEGs was performed using the LIMMA package of R (Diboun et al., 2006).
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Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/gds/
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Characteristics of datasets in this study.
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Breast Adenocarcinoma Datasets
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Table 1
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Characteristics of datasets in this study.
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Three hundred twenty-one differentially expressed genes (DEGs) were identified and confirmed from four profile datasets and the Cancer Genome Atlas (TCGA), including 203 up-regulated genes and 118 down-regulated genes in the breast cancer tissues, compared to normal breast tissues.
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Three hundred twenty-one differentially expressed genes (DEGs) were identified and confirmed from four profile datasets and the Cancer Genome Atlas (TCGA), including 203 up-regulated genes and 118 down-regulated genes in the breast cancer tissues, compared to normal breast tissues.
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S100P, COL10A1, RRM2, ADAMDEC1, UHRF1, KIF20A, GJB2, NUF2, PBK, RAB25, SPP1, DTL, SDC1, RAD51AP1, HOXC13, CKS2, UBE2C, EZH2, COL11A1, ESRP1, MMP1, SMIM22, KMO, TPX2, CEP55, MARCKSL1, CXCL10, BUB1B, FAM83D, CNTNAP2, HMMR, LMNB1, MELK, HIST1H2BD, TOP2A, KIF14, S100A14, GINS1, CDKN3, KRT8, NEK2, CXCL11, ANLN, TLCD1, CCNB1, SPAG1, TPD52, SLC44A4, SPAG5, PRC1, CDK1, EPN3, COMP, KIF11, CORO2A, SLC9A3R1, FOXM1, ZWINT, SPINT2, TRIM59, E2F5, KIF4A, TTK, HIST1H4H, NDC80, CDC7, DLGAP5, PYCR1, NUSAP1, PRSS8, SHCBP1, UBE2T, E2F8, CXCR4, PTK6, SLC12A8, MAD2L1, CCNE2, HIST1H2BH, ANKRD22, OIP5, CDC20, MNX1, HOXC10, CCNA2, TK1, ZNF367, MIF, MAL2, KIF15, CTHRC1, MCM10, ROGDI, LAMP5, UBE2S, ATAD2, CENPU, PTTG1, LRP8, TRIP13, WISP1, SULF1, AP1M2, STIL, CLDN7, NCAPG, KIF23, GGCT, ABRACL, KIF18B, SMYD3, AURKA, DEPDC1, SBK1, REM2, EVPL, CCDC167, KPNA2, TIGIT, CELSR3, PLEKHF2, PSRC1, INHBA, RMI2, C3orf80, FN1, CDCA3, NKX3-2, HMGB3, ERMP1, CENPM, FCGR1B, IL21R, C6orf99, SQLE, KIF2C, FANCI, CENPF, LLGL2, HELLS, MKI67, MMP11, RALGPS2, DDIAS, RACGAP1, ASF1B, EZR, RMI1, CAPG, MDK, ESPL1, PCNA, PLEK2, MCM2, CENPK, KNTC1,CDCA2, BARD1, POSTN, ASPM, CEMIP, PTTG3P, ZWILCH, RNF139-AS1, PLAUR, NME1, TYMS, KLHDC7B, NUP210, NEIL3, BGN, NVL, PKMYT1, MBOAT2, EDN2, ATP6V0B, ATP6AP1, POLQ, RGS4, RAD54L, LRRC15, ERCC6L, SMC4, BAIAP2L1, EXO1, SLAMF8, FEN1, SLC52A2, ICOS, PDIA4, VAMP8, HIST1H3E, ENTPD7, GPR84, CYB561, GPR19, RABIF, NOD2, MICAL2, MEX3A, FAM222A, CDCA8, ARSI
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DEFB132, LEP, PLIN1, CIDEC, ZBTB16, TIMP4, PLIN4, ACVR1C, LPL, GPAM, CFD, ITIH5, SLC19A3, LYVE1, CIDEA, AOC3, CHRDL1, FHL1, ADH1C, TNMD, KLB, MAOA, PPARG, TMEM100, C2orf40, ABCA6, CD36, FMO2, ACADL, GPR146, CA4, MRAP, PDK4, ATP1A2, MME, DMRT2, GDF10, NIPSNAP3B, SCN4B, IGFBP6, HLF, CAV1, FGF2, PCDH9, ADH1B, LRRN4CL, SLC16A7, SEMA3G, RBP7, EBF1, PPP1R14A, TSLP, TGFBR3, CORO2B, ANGPTL1, FIGN, BMP2, ANKRD29, ANXA1, COX7A1, ADAMTS5, PLAC9, PALMD, COL6A6, LINC00968, APCDD1, ASPA, SCARA5, IRS2, TMEM132C, CKMT2, SYNM, IGSF10, CCDC178, SRPX, GNG11, AKAP12, HOXA5, BTNL9, NRN1, MICU3, IL33, CFH, VIT, JAM2, ENPP2, PLSCR4, FOSB, PLAGL1, FAM149A, NR3C2, CREB5, MT1M, RERGL, MYOM1, ADRB2, PGM5-AS1, CLDN5, SPRY2, SEL1L2, ABCA9, RASSF9, FAM162B, EMCN, ITM2A, EDNRB, RBMS3, CASQ2, TSHZ2, GPC3, LHFP, SOX7, GGTA1P, ABCA8, INMT, CRYBG3, LRFN5, GSTM5
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Primer sequences used for quantitative Real-time PCR (qRT-PCR).
structure object · 5 fields
pmcid
PMC6688090
section_index
12
section_title
Quantitative Real-Time RT-PCR
row_count
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table object · 8 fields
label
Table 2
caption
Primer sequences used for quantitative Real-time PCR (qRT-PCR).
rows array · 8 items
[0] array · 2 items
[0]
Gene symbol
[1]
Primer sequence
[1] array · 2 items
[0]
CDK1
[1]
F: 5′-AAACTACAGGTCAAGTGGTAGCC-3′R: 5′-TCCTGCATAAGCACATCCTGA- 3′
[2] array · 2 items
[0]
CCNA2
[1]
F: 5′-GGATGGTAGTTTTGAGTCACCAC-3′R: 5′-CACGAGGATAGCTCTCATACTGT- 3′
[3] array · 2 items
[0]
TOP2A
[1]
F: 5′-TTAATGCTGCGGACAACAAACA-3′R: 5′-CGACCACCTGTCACTTTCTTTT- 3′
[4] array · 2 items
[0]
CCNB1
[1]
F: 5′-AATAAGGCGAAGATCAACATGGC-3′R: 5′-TTTGTTACCAATGTCCCCAAGAG- 3′
[5] array · 2 items
[0]
KIF11
[1]
F: 5′-TGTTTGATGATCCCCGTAACAAG-3′R: 5′-CTGAGTGGGAACGACTAGAGT- 3′
[6] array · 2 items
[0]
MELK
[1]
F: 5′-AACTCCAGCCTTATGCAGAAC-3′R: 5′-AACGATTTGGCGTAGTGAGTATT- 3′
[7] array · 2 items
[0]
β-Actin
[1]
F: 5′-TTGATTTTGGAGGGATCTCGCTC-3′R: 5′-GAGTCAACGGATTTGGTCGTATTG- 3′
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Three hundred twenty-one differentially expressed genes (DEGs) were identified and confirmed from four profile datasets and the Cancer Genome Atlas (TCGA), including 203 up-regulated genes and 118 down-regulated genes in the breast cancer tissues, compared to normal breast tissues.
structure object · 5 fields
pmcid
PMC6688090
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section_title
Identification of DEGs
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label
Table 3
caption
Three hundred twenty-one differentially expressed genes (DEGs) were identified and confirmed from four profile datasets and the Cancer Genome Atlas (TCGA), including 203 up-regulated genes and 118 down-regulated genes in the breast cancer tissues, compared to normal breast tissues.
rows array · 3 items
[0] array · 2 items
[0]
Regulation
[1]
DEGs (gene symbol)
[1] array · 2 items
[0]
Up-regulated
[1]
S100P, COL10A1, RRM2, ADAMDEC1, UHRF1, KIF20A, GJB2, NUF2, PBK, RAB25, SPP1, DTL, SDC1, RAD51AP1, HOXC13, CKS2, UBE2C, EZH2, COL11A1, ESRP1, MMP1, SMIM22, KMO, TPX2, CEP55, MARCKSL1, CXCL10, BUB1B, FAM83D, CNTNAP2, HMMR, LMNB1, MELK, HIST1H2BD, TOP2A, KIF14, S100A14, GINS1, CDKN3, KRT8, NEK2, CXCL11, ANLN, TLCD1, CCNB1, SPAG1, TPD52, SLC44A4, SPAG5, PRC1, CDK1, EPN3, COMP, KIF11, CORO2A, SLC9A3R1, FOXM1, ZWINT, SPINT2, TRIM59, E2F5, KIF4A, TTK, HIST1H4H, NDC80, CDC7, DLGAP5, PYCR1, NUSAP1, PRSS8, SHCBP1, UBE2T, E2F8, CXCR4, PTK6, SLC12A8, MAD2L1, CCNE2, HIST1H2BH, ANKRD22, OIP5, CDC20, MNX1, HOXC10, CCNA2, TK1, ZNF367, MIF, MAL2, KIF15, CTHRC1, MCM10, ROGDI, LAMP5, UBE2S, ATAD2, CENPU, PTTG1, LRP8, TRIP13, WISP1, SULF1, AP1M2, STIL, CLDN7, NCAPG, KIF23, GGCT, ABRACL, KIF18B, SMYD3, AURKA, DEPDC1, SBK1, REM2, EVPL, CCDC167, KPNA2, TIGIT, CELSR3, PLEKHF2, PSRC1, INHBA, RMI2, C3orf80, FN1, CDCA3, NKX3-2, HMGB3, ERMP1, CENPM, FCGR1B, IL21R, C6orf99, SQLE, KIF2C, FANCI, CENPF, LLGL2, HELLS, MKI67, MMP11, RALGPS2, DDIAS, RACGAP1, ASF1B, EZR, RMI1, CAPG, MDK, ESPL1, PCNA, PLEK2, MCM2, CENPK, KNTC1,CDCA2, BARD1, POSTN, ASPM, CEMIP, PTTG3P, ZWILCH, RNF139-AS1, PLAUR, NME1, TYMS, KLHDC7B, NUP210, NEIL3, BGN, NVL, PKMYT1, MBOAT2, EDN2, ATP6V0B, ATP6AP1, POLQ, RGS4, RAD54L, LRRC15, ERCC6L, SMC4, BAIAP2L1, EXO1, SLAMF8, FEN1, SLC52A2, ICOS, PDIA4, VAMP8, HIST1H3E, ENTPD7, GPR84, CYB561, GPR19, RABIF, NOD2, MICAL2, MEX3A, FAM222A, CDCA8, ARSI
[2] array · 2 items
[0]
Down-regulated
[1]
DEFB132, LEP, PLIN1, CIDEC, ZBTB16, TIMP4, PLIN4, ACVR1C, LPL, GPAM, CFD, ITIH5, SLC19A3, LYVE1, CIDEA, AOC3, CHRDL1, FHL1, ADH1C, TNMD, KLB, MAOA, PPARG, TMEM100, C2orf40, ABCA6, CD36, FMO2, ACADL, GPR146, CA4, MRAP, PDK4, ATP1A2, MME, DMRT2, GDF10, NIPSNAP3B, SCN4B, IGFBP6, HLF, CAV1, FGF2, PCDH9, ADH1B, LRRN4CL, SLC16A7, SEMA3G, RBP7, EBF1, PPP1R14A, TSLP, TGFBR3, CORO2B, ANGPTL1, FIGN, BMP2, ANKRD29, ANXA1, COX7A1, ADAMTS5, PLAC9, PALMD, COL6A6, LINC00968, APCDD1, ASPA, SCARA5, IRS2, TMEM132C, CKMT2, SYNM, IGSF10, CCDC178, SRPX, GNG11, AKAP12, HOXA5, BTNL9, NRN1, MICU3, IL33, CFH, VIT, JAM2, ENPP2, PLSCR4, FOSB, PLAGL1, FAM149A, NR3C2, CREB5, MT1M, RERGL, MYOM1, ADRB2, PGM5-AS1, CLDN5, SPRY2, SEL1L2, ABCA9, RASSF9, FAM162B, EMCN, ITM2A, EDNRB, RBMS3, CASQ2, TSHZ2, GPC3, LHFP, SOX7, GGTA1P, ABCA8, INMT, CRYBG3, LRFN5, GSTM5
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Hub genes with high degree of connectivity.
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17
section_title
PPI (Protein-Protein Interaction) Network and Module Analysis
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table object · 8 fields
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Table 4
caption
Hub genes with high degree of connectivity.
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[0] array · 4 items
[0]
Gene
[1]
Degree
[2]
Type
[3]
MCODE cluster
[1] array · 4 items
[0]
CDK1
[1]
78
[2]
UP
[3]
Cluster 1
[2] array · 4 items
[0]
CCNA2
[1]
72
[2]
UP
[3]
Cluster 1
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[0]
TOP2A
[1]
68
[2]
UP
[3]
Cluster 1
[4] array · 4 items
[0]
CCNB1
[1]
68
[2]
UP
[3]
Cluster 1
[5] array · 4 items
[0]
KIF11
[1]
64
[2]
UP
[3]
Cluster 1
[6] array · 4 items
[0]
MELK
[1]
64
[2]
UP
[3]
Cluster 1
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section[17]/table-wrap[1]#T4
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[0]
asset:data:geo:GSE21422 not downloaded
[1]
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[2]
asset:data:geo:GSE29431 not downloaded
[3]
asset:data:geo:GSE29431 licence not read
[4]
asset:data:geo:GSE42568 not downloaded
[5]
asset:data:geo:GSE42568 licence not read
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normalise_counts
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fdr_bh
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count_matrix_with_condition
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Identification of DEGs was performed using the LIMMA package of R (Diboun et al., 2006).
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protein-protein interaction
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GO enrichment
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method.reader_differs_from_extractor
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complete
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Automated Assays Laravel application and simulated adapters
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GSE21422
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GSE29431
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GSE42568
[3]
and GSE61304
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[0]
GSE21422
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GSE29431
[2]
GSE42568
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[0]
Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/gds/
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The paper names GSE21422, GSE29431, GSE42568 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31428132", "kind": "science-record", "revision": 8, "content_hash": "sha256:0da295c49ff53afa6c81890fe19500027ca7b8a8f3625bfbb9711a0225e3b6ee", "created_at": "2026-11-01T15:40:48Z", "updated_at": "2026-11-01T22:44:09Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis.", "doi": "10.3389/fgene.2019.00695", "pmid": "31428132", "authors": ["Jun-Li Deng", "Yun-Hua Xu", "Guo Wang"], "journal": "Frontiers in genetics", "year": 2019, "abstract": "Background: The molecular mechanism of tumorigenesis remains to be fully understood in breast cancer. It is urgently required to identify genes that are associated with breast cancer development and prognosis and to elucidate the underlying molecular mechanisms. In the present study, we aimed to identify potential pathogenic and prognostic differentially expressed genes (DEGs) in breast adenocarcinoma through bioinformatic analysis of public datasets. Methods: Four datasets (GSE21422, GSE29431, GSE42568, and GSE61304) from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) dataset were used for the bioinformatic analysis. DEGs were identified using LIMMA Package of R. The GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses were conducted through FunRich. The protein-protein interaction (PPI) network of the DEGs was established through STRING (Search Tool for the Retrieval of Interacting Genes database) website, visualized by Cytoscape and further analyzed by Molecular Complex Detection (MCODE). UALCAN and Kaplan-Meier (KM) plotter were employed to analyze the expression levels and prognostic values of hub genes. The expression levels of the hub genes were also validated in clinical samples from breast cancer patients. In addition, the gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD). Results: In total, 203 up-regulated and 118 down-regulated DEGs were identified. Mitotic cell cycle and epithelial-to-mesenchymal transition pathway were the major enriched pathways for the up-regulated and down-regulated genes, respectively. The PPI network was constructed with 314 nodes and 1,810 interactions, and two significant modules are selected. The most significant enriched pathway in module 1 was the mitotic cell cycle. Moreover, six hub genes were selected and validated in clinical sample for further analysis owing to the high degree of connectivity, including CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK, and they were all correlated to worse overall survival (OS) in breast cancer. Conclusion: These results revealed that mitotic cell cycle and epithelial-to-mesenchymal transition pathway could be potential pathways accounting for the progression in breast cancer, and CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK may be potential crucial genes. Further, it could be utilized as new biomarkers for prognosis and potential new targets for drug synthesis of breast cancer.", "claims": [{"id": "claim-method", "statement": "Identification of DEGs was performed using the LIMMA package of R (Diboun et al., 2006).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31428132", "locator": "sections[5] \"Identification of DEGs\" paragraph 2", "quote": "Identification of DEGs was performed using the LIMMA package of R (Diboun et al., 2006)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. 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Analysis", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:31428132:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:0d47158305f3fd718234fbd4a93eceba0219328b81e6dd425bb9bf8db16dd8b3", "bytes": 627, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[3]/table-wrap[1]#T1", "version": null, "note": "Characteristics of datasets in this study.", "structure": {"pmcid": "PMC6688090", "section_index": 3, "section_title": "Breast Adenocarcinoma Datasets", "row_count": 7, "column_count": 6}, "table": {"label": "Table 1", "caption": "Characteristics of datasets in this study.", "rows": [["Dataset", "Platform", "Sample", "Tumor type", "Country"], ["Normal", "Tumor"], ["GSE21422", "AffymetrixHG-U133_Plus_2", "5", "14", "Breast cancer", "Germany"], ["GSE29431", "AffymetrixHG-U133_Plus_2", "12", "54", "Breast cancer", "Spain"], ["GSE42568", "AffymetrixHG-U133_Plus_2", "17", "109", "Breast cancer", "Ireland"], ["GSE61304", "AffymetrixHG-U133_Plus_2", "4", "58", "Breast cancer", "Singapore"], ["TCGA", "IlluminaHiSeq", "113", "1,105", "Breast cancer", "USA"]], "row_count": 7, "column_count": 6, "numeric_cells": 18, "header_rows": 2, "locator": "section[3]/table-wrap[1]#T1"}}, {"id": "asset:table:pmid:31428132:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:763a566b493ab545d84dbe5c79bd970bd4b39854f8f3f1bcc26ff529f05f1097", "bytes": 2797, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[1]#T3", "version": null, "note": "Three hundred twenty-one differentially expressed genes (DEGs) were identified and confirmed from four profile datasets and the Cancer Genome Atlas (TCGA), including 203 up-regulated genes and 118 down-regulated genes in the breast cancer tissues, compared to normal breast tissues.", "structure": {"pmcid": "PMC6688090", "section_index": 5, "section_title": "Identification of DEGs", "row_count": 3, "column_count": 2}, "table": {"label": "Table 3", "caption": "Three hundred twenty-one differentially expressed genes (DEGs) were identified and confirmed from four profile datasets and the Cancer Genome Atlas (TCGA), including 203 up-regulated genes and 118 down-regulated genes in the breast cancer tissues, compared to normal breast tissues.", "rows": [["Regulation", "DEGs (gene symbol)"], ["Up-regulated", "S100P, COL10A1, RRM2, ADAMDEC1, UHRF1, KIF20A, GJB2, NUF2, PBK, RAB25, SPP1, DTL, SDC1, RAD51AP1, HOXC13, CKS2, UBE2C, EZH2, COL11A1, ESRP1, MMP1, SMIM22, KMO, TPX2, CEP55, MARCKSL1, CXCL10, BUB1B, FAM83D, CNTNAP2, HMMR, LMNB1, MELK, HIST1H2BD, TOP2A, KIF14, S100A14, GINS1, CDKN3, KRT8, NEK2, CXCL11, ANLN, TLCD1, CCNB1, SPAG1, TPD52, SLC44A4, SPAG5, PRC1, CDK1, EPN3, COMP, KIF11, CORO2A, SLC9A3R1, FOXM1, ZWINT, SPINT2, TRIM59, E2F5, KIF4A, TTK, HIST1H4H, NDC80, CDC7, DLGAP5, PYCR1, NUSAP1, PRSS8, SHCBP1, UBE2T, E2F8, CXCR4, PTK6, SLC12A8, MAD2L1, CCNE2, HIST1H2BH, ANKRD22, OIP5, CDC20, MNX1, HOXC10, CCNA2, TK1, ZNF367, MIF, MAL2, KIF15, CTHRC1, MCM10, ROGDI, LAMP5, UBE2S, ATAD2, CENPU, PTTG1, LRP8, TRIP13, WISP1, SULF1, AP1M2, STIL, CLDN7, NCAPG, KIF23, GGCT, ABRACL, KIF18B, SMYD3, AURKA, DEPDC1, SBK1, REM2, EVPL, CCDC167, KPNA2, TIGIT, CELSR3, PLEKHF2, PSRC1, INHBA, RMI2, C3orf80, FN1, CDCA3, NKX3-2, HMGB3, ERMP1, CENPM, FCGR1B, IL21R, C6orf99, SQLE, KIF2C, FANCI, CENPF, LLGL2, HELLS, MKI67, MMP11, RALGPS2, DDIAS, RACGAP1, ASF1B, EZR, RMI1, CAPG, MDK, ESPL1, PCNA, PLEK2, MCM2, CENPK, KNTC1,CDCA2, BARD1, POSTN, ASPM, CEMIP, PTTG3P, ZWILCH, RNF139-AS1, PLAUR, NME1, TYMS, KLHDC7B, NUP210, NEIL3, BGN, NVL, PKMYT1, MBOAT2, EDN2, ATP6V0B, ATP6AP1, POLQ, RGS4, RAD54L, LRRC15, ERCC6L, SMC4, BAIAP2L1, EXO1, SLAMF8, FEN1, SLC52A2, ICOS, PDIA4, VAMP8, HIST1H3E, ENTPD7, GPR84, CYB561, GPR19, RABIF, NOD2, MICAL2, MEX3A, FAM222A, CDCA8, ARSI"], ["Down-regulated", "DEFB132, LEP, PLIN1, CIDEC, ZBTB16, TIMP4, PLIN4, ACVR1C, LPL, GPAM, CFD, ITIH5, SLC19A3, LYVE1, CIDEA, AOC3, CHRDL1, FHL1, ADH1C, TNMD, KLB, MAOA, PPARG, TMEM100, C2orf40, ABCA6, CD36, FMO2, ACADL, GPR146, CA4, MRAP, PDK4, ATP1A2, MME, DMRT2, GDF10, NIPSNAP3B, SCN4B, IGFBP6, HLF, CAV1, FGF2, PCDH9, ADH1B, LRRN4CL, SLC16A7, SEMA3G, RBP7, EBF1, PPP1R14A, TSLP, TGFBR3, CORO2B, ANGPTL1, FIGN, BMP2, ANKRD29, ANXA1, COX7A1, ADAMTS5, PLAC9, PALMD, COL6A6, LINC00968, APCDD1, ASPA, SCARA5, IRS2, TMEM132C, CKMT2, SYNM, IGSF10, CCDC178, SRPX, GNG11, AKAP12, HOXA5, BTNL9, NRN1, MICU3, IL33, CFH, VIT, JAM2, ENPP2, PLSCR4, FOSB, PLAGL1, FAM149A, NR3C2, CREB5, MT1M, RERGL, MYOM1, ADRB2, PGM5-AS1, CLDN5, SPRY2, SEL1L2, ABCA9, RASSF9, FAM162B, EMCN, ITM2A, EDNRB, RBMS3, CASQ2, TSHZ2, GPC3, LHFP, SOX7, GGTA1P, ABCA8, INMT, CRYBG3, LRFN5, GSTM5"]], "row_count": 3, "column_count": 2, "numeric_cells": 2, "header_rows": 1, "locator": "section[15]/table-wrap[1]#T3"}}, {"id": "asset:table:pmid:31428132:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:ec45151c80b7aa7c0b5947015277c9a65a2ddc51f1292d2b4d3217a86c8d9351", "bytes": 840, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[12]/table-wrap[1]#T2", "version": null, "note": "Primer sequences used for quantitative Real-time PCR (qRT-PCR).", "structure": {"pmcid": "PMC6688090", "section_index": 12, "section_title": "Quantitative Real-Time RT-PCR", "row_count": 8, "column_count": 2}, "table": {"label": "Table 2", "caption": "Primer sequences used for quantitative Real-time PCR (qRT-PCR).", "rows": [["Gene symbol", "Primer sequence"], ["CDK1", "F: 5′-AAACTACAGGTCAAGTGGTAGCC-3′R: 5′-TCCTGCATAAGCACATCCTGA- 3′"], ["CCNA2", "F: 5′-GGATGGTAGTTTTGAGTCACCAC-3′R: 5′-CACGAGGATAGCTCTCATACTGT- 3′"], ["TOP2A", "F: 5′-TTAATGCTGCGGACAACAAACA-3′R: 5′-CGACCACCTGTCACTTTCTTTT- 3′"], ["CCNB1", "F: 5′-AATAAGGCGAAGATCAACATGGC-3′R: 5′-TTTGTTACCAATGTCCCCAAGAG- 3′"], ["KIF11", "F: 5′-TGTTTGATGATCCCCGTAACAAG-3′R: 5′-CTGAGTGGGAACGACTAGAGT- 3′"], ["MELK", "F: 5′-AACTCCAGCCTTATGCAGAAC-3′R: 5′-AACGATTTGGCGTAGTGAGTATT- 3′"], ["β-Actin", "F: 5′-TTGATTTTGGAGGGATCTCGCTC-3′R: 5′-GAGTCAACGGATTTGGTCGTATTG- 3′"]], "row_count": 8, "column_count": 2, "numeric_cells": 8, "header_rows": 1, "locator": "section[12]/table-wrap[1]#T2"}}, {"id": "asset:table:pmid:31428132:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:763a566b493ab545d84dbe5c79bd970bd4b39854f8f3f1bcc26ff529f05f1097", "bytes": 2797, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[1]#T3", "version": null, "note": "Three hundred twenty-one differentially expressed genes (DEGs) were identified and confirmed from four profile datasets and the Cancer Genome Atlas (TCGA), including 203 up-regulated genes and 118 down-regulated genes in the breast cancer tissues, compared to normal breast tissues.", "structure": {"pmcid": "PMC6688090", "section_index": 15, "section_title": "Identification of DEGs", "row_count": 3, "column_count": 2}, "table": {"label": "Table 3", "caption": "Three hundred twenty-one differentially expressed genes (DEGs) were identified and confirmed from four profile datasets and the Cancer Genome Atlas (TCGA), including 203 up-regulated genes and 118 down-regulated genes in the breast cancer tissues, compared to normal breast tissues.", "rows": [["Regulation", "DEGs (gene symbol)"], ["Up-regulated", "S100P, COL10A1, RRM2, ADAMDEC1, UHRF1, KIF20A, GJB2, NUF2, PBK, RAB25, SPP1, DTL, SDC1, RAD51AP1, HOXC13, CKS2, UBE2C, EZH2, COL11A1, ESRP1, MMP1, SMIM22, KMO, TPX2, CEP55, MARCKSL1, CXCL10, BUB1B, FAM83D, CNTNAP2, HMMR, LMNB1, MELK, HIST1H2BD, TOP2A, KIF14, S100A14, GINS1, CDKN3, KRT8, NEK2, CXCL11, ANLN, TLCD1, CCNB1, SPAG1, TPD52, SLC44A4, SPAG5, PRC1, CDK1, EPN3, COMP, KIF11, CORO2A, SLC9A3R1, FOXM1, ZWINT, SPINT2, TRIM59, E2F5, KIF4A, TTK, HIST1H4H, NDC80, CDC7, DLGAP5, PYCR1, NUSAP1, PRSS8, SHCBP1, UBE2T, E2F8, CXCR4, PTK6, SLC12A8, MAD2L1, CCNE2, HIST1H2BH, ANKRD22, OIP5, CDC20, MNX1, HOXC10, CCNA2, TK1, ZNF367, MIF, MAL2, KIF15, CTHRC1, MCM10, ROGDI, LAMP5, UBE2S, ATAD2, CENPU, PTTG1, LRP8, TRIP13, WISP1, SULF1, AP1M2, STIL, CLDN7, NCAPG, KIF23, GGCT, ABRACL, KIF18B, SMYD3, AURKA, DEPDC1, SBK1, REM2, EVPL, CCDC167, KPNA2, TIGIT, CELSR3, PLEKHF2, PSRC1, INHBA, RMI2, C3orf80, FN1, CDCA3, NKX3-2, HMGB3, ERMP1, CENPM, FCGR1B, IL21R, C6orf99, SQLE, KIF2C, FANCI, CENPF, LLGL2, HELLS, MKI67, MMP11, RALGPS2, DDIAS, RACGAP1, ASF1B, EZR, RMI1, CAPG, MDK, ESPL1, PCNA, PLEK2, MCM2, CENPK, KNTC1,CDCA2, BARD1, POSTN, ASPM, CEMIP, PTTG3P, ZWILCH, RNF139-AS1, PLAUR, NME1, TYMS, KLHDC7B, NUP210, NEIL3, BGN, NVL, PKMYT1, MBOAT2, EDN2, ATP6V0B, ATP6AP1, POLQ, RGS4, RAD54L, LRRC15, ERCC6L, SMC4, BAIAP2L1, EXO1, SLAMF8, FEN1, SLC52A2, ICOS, PDIA4, VAMP8, HIST1H3E, ENTPD7, GPR84, CYB561, GPR19, RABIF, NOD2, MICAL2, MEX3A, FAM222A, CDCA8, ARSI"], ["Down-regulated", "DEFB132, LEP, PLIN1, CIDEC, ZBTB16, TIMP4, PLIN4, ACVR1C, LPL, GPAM, CFD, ITIH5, SLC19A3, LYVE1, CIDEA, AOC3, CHRDL1, FHL1, ADH1C, TNMD, KLB, MAOA, PPARG, TMEM100, C2orf40, ABCA6, CD36, FMO2, ACADL, GPR146, CA4, MRAP, PDK4, ATP1A2, MME, DMRT2, GDF10, NIPSNAP3B, SCN4B, IGFBP6, HLF, CAV1, FGF2, PCDH9, ADH1B, LRRN4CL, SLC16A7, SEMA3G, RBP7, EBF1, PPP1R14A, TSLP, TGFBR3, CORO2B, ANGPTL1, FIGN, BMP2, ANKRD29, ANXA1, COX7A1, ADAMTS5, PLAC9, PALMD, COL6A6, LINC00968, APCDD1, ASPA, SCARA5, IRS2, TMEM132C, CKMT2, SYNM, IGSF10, CCDC178, SRPX, GNG11, AKAP12, HOXA5, BTNL9, NRN1, MICU3, IL33, CFH, VIT, JAM2, ENPP2, PLSCR4, FOSB, PLAGL1, FAM149A, NR3C2, CREB5, MT1M, RERGL, MYOM1, ADRB2, PGM5-AS1, CLDN5, SPRY2, SEL1L2, ABCA9, RASSF9, FAM162B, EMCN, ITM2A, EDNRB, RBMS3, CASQ2, TSHZ2, GPC3, LHFP, SOX7, GGTA1P, ABCA8, INMT, CRYBG3, LRFN5, GSTM5"]], "row_count": 3, "column_count": 2, "numeric_cells": 2, "header_rows": 1, "locator": "section[15]/table-wrap[1]#T3"}}, {"id": "asset:table:pmid:31428132:5", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:6db1db76899ed30eee90d6b1eb722dcf644583933aad0bcfb8ee23ffeb936dca", "bytes": 422, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[17]/table-wrap[1]#T4", "version": null, "note": "Hub genes with high degree of connectivity.", "structure": {"pmcid": "PMC6688090", "section_index": 17, "section_title": "PPI (Protein-Protein Interaction) Network and Module Analysis", "row_count": 7, "column_count": 4}, "table": {"label": "Table 4", "caption": "Hub genes with high degree of connectivity.", "rows": [["Gene", "Degree", "Type", "MCODE cluster"], ["CDK1", "78", "UP", "Cluster 1"], ["CCNA2", "72", "UP", "Cluster 1"], ["TOP2A", "68", "UP", "Cluster 1"], ["CCNB1", "68", "UP", "Cluster 1"], ["KIF11", "64", "UP", "Cluster 1"], ["MELK", "64", "UP", "Cluster 1"]], "row_count": 7, "column_count": 4, "numeric_cells": 13, "header_rows": 1, "locator": "section[17]/table-wrap[1]#T4"}}], "gaps": ["asset:data:geo:GSE21422 not downloaded", "asset:data:geo:GSE21422 licence not read", "asset:data:geo:GSE29431 not downloaded", "asset:data:geo:GSE29431 licence not read", "asset:data:geo:GSE42568 not downloaded", "asset:data:geo:GSE42568 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Identification of DEGs was performed using the LIMMA package of R (Diboun et al., 2006)."}}, {"id": "method-2", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}, {"id": "method-3", "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"}}, {"id": "method-4", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "GO enrichment"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "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": ["GSE21422", "GSE29431", "GSE42568", "and GSE61304"], "resolved_accessions": ["GSE21422", "GSE29431", "GSE42568"], "statements": ["Publicly available datasets were analyzed in this study. This data can be found here: https://www.ncbi.nlm.nih.gov/gds/"], "basis": "The paper names GSE21422, GSE29431, GSE42568 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:31428132", "data:geo:GSE21422", "asset:table:pmid:31428132:1", "asset:table:pmid:31428132:2", "asset:table:pmid:31428132:3", "asset:table:pmid:31428132:4", "asset:table:pmid:31428132:5"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE21422"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:16:03Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 26631, "completion_tokens": 2375, "cached_tokens": 792}}, "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:31428132", "type": "paper", "label": "pmid:31428132"}, {"id": "source:pmid:31428132", "type": "manuscript", "label": "PMID 31428132 full text"}, {"id": "data:geo:GSE21422", "type": "dataset", "label": "GEO GSE21422"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:31428132", "type": "paper", "label": "pmid:31428132"}, {"id": "source:pmid:31428132", "type": "manuscript", "label": "PMID 31428132 full text"}, {"id": "data:geo:GSE21422", "type": "dataset", "label": "GEO GSE21422"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-31428132", "type": "extraction", "used": ["source:pmid:31428132"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE21422", "type": "accession_resolution", "used": ["data:geo:GSE21422"], "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:31428132", "parent_hash": "sha256:63125f6bb54588baab17c1805752b510e622793d3de62f6cbaef495deacc1931", "fork_of": null, "generation": 7}, "gaps": ["asset:data:geo:GSE21422 licence not read", "asset:data:geo:GSE21422 not downloaded", "asset:data:geo:GSE29431 licence not read", "asset:data:geo:GSE29431 not downloaded", "asset:data:geo:GSE42568 licence not read", "asset:data:geo:GSE42568 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Identification of DEGs was performed using the LIMMA package of R (Diboun et al., 2006)."], "order_basis": "analysis_only", "id": "assay:1"}]}