← All .science files
pmid:32608553
Identification of functional long non-coding RNAs in gastric cancer by bioinformatics analysis.
Yang Li · Dongyang Ma · Tang Li · Yuan Yin
International journal of experimental pathology · 2020 doi:10.1111/iep.12350
Paper
complete
Experiment
complete
Data
partial
Analysis
partial
Execution
absent
Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
paper object · 10 fields
authors array · 4 items
claims array · 3 items
[0] object · 6 fields
evidence array · 1 item
[0] object · 3 fields
[1] object · 6 fields
evidence array · 1 item
[0] object · 3 fields
[2] object · 6 fields
evidence array · 2 items
[0] object · 3 fields
[1] object · 3 fields
gaps array · 0 items
experiment object · 8 fields
steps array · 3 items
[0] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
[1] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
[2] object · 13 fields
parameters object · 0 fields
inputs array · 1 item
outputs array · 1 item
instruments array · 0 items
reagents array · 0 items
materials array · 0 items
instruments array · 0 items
reagents array · 0 items
conditions object · 0 fields
gaps array · 0 items
data object · 3 fields
assets array · 2 items
[0] object · 15 fields
structure object · 4 fields
[1] object · 15 fields
structure object · 15 fields
sample_accessions array · 200 items
gaps array · 2 items
analysis object · 4 fields
methods array · 1 item
[0] object · 10 fields
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
targets array · 0 items
gaps array · 1 item
capability object · 3 fields
requirements array · 1 item
[0] object · 6 fields
assay_families array · 9 items
gaps array · 0 items
readiness object · 8 fields
axes object · 3 fields
method object · 5 fields
required_operations array · 0 items
missing_operations array · 0 items
capability object · 4 fields
data object · 6 fields
accessions array · 1 item
resolved_accessions array · 1 item
statements array · 1 item
can_run object · 3 fields
dsl_operations array · 0 items
assets array · 2 items
steps array · 1 item
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
gaps array · 1 item
review object · 5 fields
machine_critique object · 5 fields
reader object · 5 fields
evidence_check object · 2 fields
usage object · 3 fields
stages array · 1 item
[0] object · 4 fields
gaps array · 3 items
provenance object · 7 fields
entities array · 3 items
activities array · 3 items
[0] object · 4 fields
used array · 3 items
[0] object · 3 fields
[1] object · 3 fields
[2] object · 3 fields
[1] object · 4 fields
agents array · 2 items
lineage object · 4 fields
gaps array · 7 items
Complete file
{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32608553", "kind": "science-record", "revision": 3, "content_hash": "sha256:65f180f1b80286d2c96854089b60d8d148d1ed6377ca2edbcfc461d69d0eeb09", "created_at": "2026-11-01T17:33:49Z", "updated_at": "2026-11-01T21:23:26Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of functional long non-coding RNAs in gastric cancer by bioinformatics analysis.", "doi": "10.1111/iep.12350", "pmid": "32608553", "authors": ["Yang Li", "Dongyang Ma", "Tang Li", "Yuan Yin"], "journal": "International journal of experimental pathology", "year": 2020, "abstract": "Long non-coding RNAs (lncRNAs) have been proven to play important roles in various cancers, including gastric cancer (GC). However, detailed knowledge about lncRNAs in GC is limited. Therefore we carried out an in-depth study of public data and found 83 differently expressed lncRNAs in GC. To further confirm the target genes of these lncRNAs, we constructed a co-expression network between lncRNAs and mRNAs and found three lncRNAs (MBNL1-AS1, HAND2-AS1 and MIR100HG) were at the core of the network. By coalition analysis of clinical information and the three lncRNAs' expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor. Clinical samples showed patients with higher MIR100HG expression had poorer prognosis, and further experiments demonstrated that MIR100HG was associated with proliferation, migration and invasion of GC cells. Hopefully, MIR100HG might be considered as a novel prognostic factor and biomarker for GC.", "claims": [{"id": "claim-method", "statement": "By coalition analysis of clinical information and the three lncRNAs’ expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32608553", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "By coalition analysis of clinical information and the three lncRNAs’ expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor."}], "state": "complete"}, {"id": "claim-data-access", "statement": "By coalition analysis of clinical information and the three lncRNAs’ expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32608553", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "By coalition analysis of clinical information and the three lncRNAs’ expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor."}], "state": "complete"}, {"id": "claim-target-result", "statement": "MIR100HG could be a potential prognostic factor for gastric cancer, with higher expression associated with poorer prognosis and with proliferation, migration, and invasion of gastric cancer cells.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:32608553", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "By coalition analysis of clinical information and the three lncRNAs’ expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor."}, {"asset": "source:pmid:32608553", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Clinical samples showed patients with higher MIR100HG expression had poorer prognosis, and further experiments demonstrated that MIR100HG was associated with proliferation, migration and invasion of GC cells."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "MIR100HG could be a potential prognostic factor for gastric cancer, with higher expression associated with poorer prognosis and with proliferation, migration, and invasion of gastric cancer cells.", "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:32608553"], "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:GSE15459"], "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:GSE15459"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32608553", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1111/iep.12350", "sha256": "sha256:fd00a196596ec1a8e34dbc07af2cc21bb01098aa0c2b74ba5951f25fe6c29d1c", "bytes": 1019, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1111/iep.12350", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7370847", "source": "ncbi_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE15459", "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=GSE15459", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE15459", "version": null, "note": "By coalition analysis of clinical information and the three lncRNAs’ expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "By coalition analysis of clinical information and the three lncRNAs’ expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM387788", "GSM387789", "GSM387790", "GSM387791", "GSM387792", "GSM387793", "GSM387794", "GSM387795", "GSM387796", "GSM387797", "GSM387798", "GSM387799", "GSM387800", "GSM387801", "GSM387802", "GSM387803", "GSM387804", "GSM387805", "GSM387806", "GSM387807", "GSM387808", "GSM387809", "GSM387810", "GSM387811", "GSM387812", "GSM387813", "GSM387814", "GSM387815", "GSM387816", "GSM387817", "GSM387818", "GSM387819", "GSM387820", "GSM387821", "GSM387822", "GSM387823", "GSM387824", "GSM387825", "GSM387826", "GSM387827", "GSM387828", "GSM387829", "GSM387830", "GSM387831", "GSM387832", "GSM387833", "GSM387834", "GSM387835", "GSM387836", "GSM387837", "GSM387838", "GSM387839", "GSM387840", "GSM387841", "GSM387842", "GSM387843", "GSM387844", "GSM387845", "GSM387846", "GSM387847", "GSM387848", "GSM387849", "GSM387850", "GSM387851", "GSM387852", "GSM387853", "GSM387854", "GSM387855", "GSM387856", "GSM387857", "GSM387858", "GSM387859", "GSM387860", "GSM387861", "GSM387862", "GSM387863", "GSM387864", "GSM387865", "GSM387866", "GSM387867", "GSM387868", "GSM387869", "GSM387870", "GSM387871", "GSM387872", "GSM387873", "GSM387874", "GSM387875", "GSM387876", "GSM387877", "GSM387878", "GSM387879", "GSM387880", "GSM387881", "GSM387882", "GSM387883", "GSM387884", "GSM387885", "GSM387886", "GSM387887", "GSM387888", "GSM387889", "GSM387890", "GSM387891", "GSM387892", "GSM387893", "GSM387894", "GSM387895", "GSM387896", "GSM387897", "GSM387898", "GSM387899", "GSM387900", "GSM387901", "GSM387902", "GSM387903", "GSM387904", "GSM387905", "GSM387906", "GSM387907", "GSM387908", "GSM387909", "GSM387910", "GSM387911", "GSM387912", "GSM387913", "GSM387914", "GSM387915", "GSM387916", "GSM387917", "GSM387918", "GSM387919", "GSM387920", "GSM387921", "GSM387922", "GSM387923", "GSM387924", "GSM387925", "GSM387926", "GSM387927", "GSM387928", "GSM387929", "GSM387930", "GSM387931", "GSM387932", "GSM387933", "GSM387934", "GSM387935", "GSM387936", "GSM387937", "GSM387938", "GSM387939", "GSM387940", "GSM387941", "GSM387942", "GSM387943", "GSM387944", "GSM387945", "GSM387946", "GSM387947", "GSM387948", "GSM387949", "GSM387950", "GSM387951", "GSM387952", "GSM387953", "GSM387954", "GSM387955", "GSM387956", "GSM387957", "GSM387958", "GSM387959", "GSM387960", "GSM387961", "GSM387962", "GSM387963", "GSM387964", "GSM387965", "GSM387966", "GSM387967", "GSM387968", "GSM387969", "GSM387970", "GSM387971", "GSM387972", "GSM387973", "GSM387974", "GSM387975", "GSM387976", "GSM387977", "GSM387978", "GSM387979", "GSM387980", "GSM387981", "GSM387982", "GSM387983", "GSM387984", "GSM387985", "GSM387986", "GSM387987"], "sample_count": 200, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gastric Cancer Project '08 (Singapore Patient Cohort)", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE15459 not downloaded", "asset:data:geo:GSE15459 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": null, "specific": null, "label": "coalition analysis", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "By coalition analysis of clinical information and the three lncRNAs’ expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "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": "blocked", "tier": "R4", "blocking_axis": "method", "blocked_on": "method:not_determinable", "axes": {"method": {"tier": "R4", "expressible": false, "required_operations": [], "missing_operations": [], "basis": "The reader quoted the method the paper names (coalition analysis), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible."}, "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": ["GSE15459"], "resolved_accessions": ["GSE15459"], "statements": ["By coalition analysis of clinical information and the three lncRNAs’ expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor."], "basis": "The paper names GSE15459 in GSE15459 and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:32608553", "data:geo:GSE15459"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE15459"]}, "gaps": ["method:not_determinable"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:00:11Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 1860, "completion_tokens": 1146, "cached_tokens": 128}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:32608553", "type": "paper", "label": "pmid:32608553"}, {"id": "source:pmid:32608553", "type": "manuscript", "label": "PMID 32608553 full text"}, {"id": "data:geo:GSE15459", "type": "dataset", "label": "GEO GSE15459"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:32608553", "type": "paper", "label": "pmid:32608553"}, {"id": "source:pmid:32608553", "type": "manuscript", "label": "PMID 32608553 full text"}, {"id": "data:geo:GSE15459", "type": "dataset", "label": "GEO GSE15459"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-32608553", "type": "extraction", "used": ["source:pmid:32608553"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE15459", "type": "accession_resolution", "used": ["data:geo:GSE15459"], "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:32608553", "parent_hash": "sha256:1b308781274a2b179e605a6de5fefa987148e5e143ecfbafde1da56a16e29c4c", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE15459 licence not read", "asset:data:geo:GSE15459 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"]}