← All .science files
pmid:31372408
Human tear fluid proteome dataset for usage as a spectral library and for protein modeling.
Annika Guntermann · Simone Steinbach · Bettina Serschnitzki · Pia Grotegut · Sabrina Reinehr · Stephanie C Joachim · Marc Schargus · Katrin Marcus · Caroline May
Data in brief · 2019 doi:10.1016/j.dib.2019.103742
Paper
complete
Experiment
complete
Data
partial
Analysis
absent
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 · 9 items
claims array · 1 item
[0] object · 6 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 · 4 items
[0] object · 15 fields
structure object · 4 fields
[1] object · 15 fields
structure object · 15 fields
sample_accessions array · 0 items
[2] object · 16 fields
structure object · 5 fields
table object · 8 fields
rows array · 10 items
[0] array · 3 items
[1] array · 3 items
[2] array · 3 items
[3] array · 3 items
[4] array · 3 items
[5] array · 3 items
[6] array · 3 items
[7] array · 3 items
[8] array · 3 items
[9] array · 3 items
[3] object · 16 fields
structure object · 5 fields
table object · 8 fields
rows array · 10 items
[0] array · 3 items
[1] array · 3 items
[2] array · 3 items
[3] array · 3 items
[4] array · 3 items
[5] array · 3 items
[6] array · 3 items
[7] array · 3 items
[8] array · 3 items
[9] array · 3 items
gaps array · 2 items
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 · 4 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 · 8 items
assays array · 1 item
[0] object · 11 fields
required_operations array · 0 items
source_hashes object · 1 field
evidence array · 4 items
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31372408", "kind": "science-record", "revision": 3, "content_hash": "sha256:bac4faea580443f07b9c104a5fbf3c74e7e51f56a1165f0fa4dede50df4b8a0c", "created_at": "2026-11-01T15:40:48Z", "updated_at": "2026-11-01T18:51:07Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Human tear fluid proteome dataset for usage as a spectral library and for protein modeling.", "doi": "10.1016/j.dib.2019.103742", "pmid": "31372408", "authors": ["Annika Guntermann", "Simone Steinbach", "Bettina Serschnitzki", "Pia Grotegut", "Sabrina Reinehr", "Stephanie C Joachim", "Marc Schargus", "Katrin Marcus", "Caroline May"], "journal": "Data in brief", "year": 2019, "abstract": "This article provides a detailed dataset of human tear fluid proteins. Samples were fractionated by sodium dodecyl sulfate (SDS) gel electrophoresis resulting in 48 fractions that were spiked with an indexed retention time (iRT) peptide standard. These data are based on a data-dependent acquisition (DDA) mass spectrometric approach and can be used for example as a spectral library for tear fluid proteome analysis by data-independent acquisition (DIA). Moreover, the provided data set can be used with optimized HPLC and mass spectrometric settings for proteins/peptides of interest. Besides these aspects, this dataset can serve as a protein overview for gene ontology enrichment analysis and for modeling and benchmarking of multiple signaling pathways associated with the ocular surface in healthy or disease stages. The mass spectrometry proteomics data from the described workflow have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD011075.", "claims": [{"id": "claim-data-access", "statement": "The mass spectrometry proteomics data from the described workflow have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD011075.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31372408", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The mass spectrometry proteomics data from the described workflow have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD011075."}], "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:31372408"], "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:PXD011075"], "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:PXD011075"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:31372408", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.dib.2019.103742", "sha256": "sha256:083c0de109e8a5615c34a91cbfb07a0299c06a08051b10376ad84db37bf5cb75", "bytes": 13253, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.dib.2019.103742", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6660621", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:PXD011075", "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=PXD011075", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "PXD011075", "version": null, "note": "The mass spectrometry proteomics data from the described workflow have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD011075.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The mass spectrometry proteomics data from the described workflow have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD011075.", "access_statement_kind": "data_availability_statement", "sample_accessions": [], "sample_count": null, "group_sizes": null, "group_sizes_basis": null, "platform": null, "taxon": null, "title": "Human tear fluid proteome dataset for usage as a spectral library and for protein modeling", "resolution_checked_at": "2026-10-31T18:35:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:31372408:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:24d82abea78b36b848f4189803c1dfc9c315fafb28e292767a9b6c4d13b65d7b", "bytes": 442, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[6]/table-wrap[1]#tbl1", "version": null, "note": "Solvent gradient profile for the elution of amino acids.", "structure": {"pmcid": "PMC6660621", "section_index": 6, "section_title": "Amino acid analysis", "row_count": 10, "column_count": 3}, "table": {"label": "Table 1", "caption": "Solvent gradient profile for the elution of amino acids.", "rows": [["Time [min]", "% Eluent A", "% Eluent B"], ["0", "99.9", "0.1"], ["0.54", "99.9", "0.1"], ["5.74", "90.9", "0.1"], ["7.74", "78.8", "21.2"], ["8.04", "40.4", "59.6"], ["8.05", "10.0", "90"], ["8.64", "10.0", "90"], ["8.73", "99.9", "0.1"], ["9.50", "99.9", "0.1"]], "row_count": 10, "column_count": 3, "numeric_cells": 27, "header_rows": 1, "locator": "section[6]/table-wrap[1]#tbl1"}}, {"id": "asset:table:pmid:31372408:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:312999e2a123d01f81b280f8e2b29a1626ee52028eeab065ba64b37a0f57f842", "bytes": 473, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[10]/table-wrap[1]#tbl2", "version": null, "note": "Solvent gradient profile for elution of peptides.", "structure": {"pmcid": "PMC6660621", "section_index": 10, "section_title": "NanoHPLC settings", "row_count": 10, "column_count": 3}, "table": {"label": "Table 2", "caption": "Solvent gradient profile for elution of peptides.", "rows": [["Time [min]", "% Eluent A", "% Eluent B"], ["0.00", "95.00", "5.00"], ["7.00", "95.00", "5.00"], ["15.00", "85.00", "15.00"], ["122.00", "60.00", "40.00"], ["127.00", "40.00", "60.00"], ["128.00", "5.00", "95.00"], ["133.00", "5.00", "95.00"], ["138.00", "95.00", "5.00"], ["150.00", "95.00", "5.00"]], "row_count": 10, "column_count": 3, "numeric_cells": 27, "header_rows": 1, "locator": "section[10]/table-wrap[1]#tbl2"}}], "gaps": ["asset:data:geo:PXD011075 not downloaded", "asset:data:geo:PXD011075 licence not read"]}, "analysis": {"state": "absent", "methods": [], "targets": [], "gaps": ["method", "operations"]}, "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 (not named), 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": ["PXD011075"], "resolved_accessions": ["PXD011075"], "statements": ["The mass spectrometry proteomics data from the described workflow have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD011075."], "basis": "The paper names PXD011075 in ProteomeXchange Consortium via the PRIDE partner repository and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:31372408", "data:geo:PXD011075", "asset:table:pmid:31372408:1", "asset:table:pmid:31372408:2"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:PXD011075"]}, "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": "2026-10-31T18:15:36Z", "independence": "single_reader"}, "evidence_check": {"method": null, "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 11562, "completion_tokens": 887, "cached_tokens": 384}}, "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:31372408", "type": "paper", "label": "pmid:31372408"}, {"id": "source:pmid:31372408", "type": "manuscript", "label": "PMID 31372408 full text"}, {"id": "data:geo:PXD011075", "type": "dataset", "label": "GEO PXD011075"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:31372408", "type": "paper", "label": "pmid:31372408"}, {"id": "source:pmid:31372408", "type": "manuscript", "label": "PMID 31372408 full text"}, {"id": "data:geo:PXD011075", "type": "dataset", "label": "GEO PXD011075"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-31372408", "type": "extraction", "used": ["source:pmid:31372408"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-PXD011075", "type": "accession_resolution", "used": ["data:geo:PXD011075"], "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:31372408", "parent_hash": "sha256:66cbb8b5fa473eb5fdca5fad804ae0da41877638f78a80d49a3b258296352b99", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:PXD011075 licence not read", "asset:data:geo:PXD011075 not downloaded", "execution.not_run", "method", "operations", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "mass_spectrometry", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["based on a data-dependent acquisition (DDA) mass spectrometric approach and can be used for example as a sp", "data set can be used with optimized HPLC and mass spectrometric settings for proteins/peptides of interest.", "ar surface in healthy or disease stages. The mass spectrometry proteomics data from the described workflow", "thy or disease stages. The mass spectrometry proteomics data from the described workflow have been d"], "order_basis": "paper_text_order:354", "id": "assay:1"}]}