{"doi":"10.1126/sciadv.adv1971","title":"Learning the rules of peptide self-assembly through data mining with large language models","abstract":"Peptides are ubiquitous and important biomolecules that self-assemble into diverse structures. Although extensive research has explored the effects of chemical composition and exterior conditions on self-assembly, a systematic study consolidating these data to uncover global rules is lacking. In this work, we curate a peptide assembly database through a combination of manual processing by human experts and large language model-assisted literature mining. As a result, we collect over 1000 experimental data entries with information about peptide sequence, experimental conditions, and corresponding self-assembly phases. Using the data, machine learning models are developed, demonstrating excellent accuracy (>80%) in assembly phase classification. Moreover, we fine-tune a GPT model for peptide literature mining with the developed dataset, which markedly outperforms the pretrained model in extracting information from academic publications. This workflow can improve efficiency when exploring potential self-assembling peptide candidates, through guiding experimental work, while also deepening our understanding of the governing mechanisms.","journal":"Science Advances","year":2025,"id":510449,"datarank":0.5181574969734952,"base_score":3.044522437723423,"endowment":3.044522437723423,"self_citation_contribution":0.4566783656585135,"citation_network_contribution":0.06147913131498176,"self_endowment_contribution":0.4566783656585135,"citer_contribution":0.06147913131498176,"corpus_percentile":62.65954977953121,"corpus_rank":4828,"citation_count":20,"citer_count":19,"citers_with_citation_signal":9,"citers_with_endowment":9,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.7289,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":50.0,"fair_percentile":62.702537450321,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1366793,"name":"Sarah K. Yorke","orcid":"0000-0002-3511-4222","position":1,"is_corresponding":false},{"id":353384,"name":"Tuomas P. J. Knowles","orcid":"0000-0002-7879-0140","position":2,"is_corresponding":false},{"id":109876,"name":"Markus J. Buehler","orcid":"0000-0002-4173-9659","position":3,"is_corresponding":false},{"id":109874,"name":"Zhenze Yang","orcid":"0000-0002-6427-6757","position":0,"is_corresponding":true}],"reference_count":69,"raw_metadata":null,"created_at":"2026-07-19T02:47:36.538276Z","pmid":"40138415","pmcid":"PMC11939049","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":77.7778,"fair_a":25.0,"fair_i":0.0,"fair_r":25.0,"fair_zscore":0.6155,"fair_rationale":{"fair_score":50.0,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":77.78,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"10.5281/zenodo.14791268","grounded":true,"rationale":"The paper provides a DOI for its dataset, which is a persistent identifier scheme.","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"Zenodo","grounded":true,"rationale":"The paper names Zenodo as the repository holding the data. [majority verdict 'yes' (4/5 passes agreed)]","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"All data needed to evaluate the conclusions in this paper are present in the paper and/or the Supplementary Materials. All data and codes are published online on Zenodo (DOI: 10.5281/zenodo.14791268).","grounded":false,"rationale":"The statement points to a repository record with a DOI (Colavizza category 3). [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","anchors":["Colavizza, Hrynaszkiewicz, Staden, Whitaker & McGillivray (2020), 'The citation advantage of li","Springer Nature research data policy — Data Availability Statements: standard statement templat","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes"],"scored":false,"signal":null},{"key":"f_discovery_metadata","label":"Description of the dataset as an object","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"Example data entries in the database are shown in table S1.","grounded":true,"rationale":"The paper references a supplementary table that lists example data entries, serving as an itemised inventory.","anchors":["RDA-F2-01M — 'Rich metadata is provided to allow discovery' (priority Essential)","FsF-F2-01M — F-UJI: 'Metadata includes descriptive core elements to support data findability'","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'"],"scored":false,"signal":null},{"key":"f_dataset_cited","label":"Dataset formally cited","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":"All data and codes are published online on Zenodo (DOI: 10.5281/zenodo.14791268).","grounded":false,"rationale":"The dataset's identifier appears only in the body text, not as a reference-list entry. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","anchors":["FORCE11 Joint Declaration of Data Citation Principles (2014) — data should be cited as a first-","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes","FsF-F3-01M — F-UJI: 'Metadata includes the identifier of the data it describes'"],"scored":true,"signal":null}]},"A":{"name":"Accessible","score":25.0,"criteria":[{"key":"a_data_openly_accessible","label":"Access route free of preconditions","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"All data and codes are published online on Zenodo (DOI: 10.5281/zenodo.14791268).","grounded":false,"rationale":"The text gives a route to the data with no stated precondition. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","anchors":["RDA-A1.1-01D — 'Data is accessible through a free access protocol'","FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data'","NSTC Desirable Characteristics of Data Repositories (2022) — 'Free and Easy Access'"],"scored":true,"signal":null},{"key":"a_access_conditions_stated","label":"Access level labelled","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":"All data and codes are published online on Zenodo (DOI: 10.5281/zenodo.14791268).","grounded":false,"rationale":"The paper describes the action of publishing on Zenodo but does not explicitly label the access level (e.g., 'open access') for the data. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","anchors":["FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data'","RDA-A1-01M — metadata contains information to enable the user to get access to the data","COAR Controlled Vocabularies — Access Rights v1.0 (open / embargoed / restricted / metadata-onl"],"scored":false,"signal":null},{"key":"a_controlled_access_for_sensitive","label":"Gatekeeper for sensitive data","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The data are not sensitive or human-subject, and no gatekeeper is named.","anchors":["NIH Genomic Data Sharing Policy (NOT-OD-14-124) — controlled-access via a Data Access Committee","RDA-A1.2-01D — 'Data is accessible through an access protocol that supports authentication and ","NIH DMS Policy Element 5 (NOT-OD-21-014) — Access, Distribution, or Reuse Considerations (conse"],"scored":false,"signal":null},{"key":"a_timeline_retention","label":"Availability timing & retention","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No sentence states when the data become available or how long they persist. [majority verdict 'no' (4/5 passes agreed)]","anchors":["NIH DMS Plan Element 4 (NOT-OD-21-014) — Data Preservation, Access, and Associated Timelines","NSTC Desirable Characteristics (2022), Organizational Infrastructure: 'Retention Policy'","RDA-A2-01M — 'Metadata is guaranteed to remain available after data is no longer available'"],"scored":false,"signal":null}]},"I":{"name":"Interoperable","score":0.0,"criteria":[{"key":"i_open_nonproprietary_format","label":"Open file format","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No file format is named for the released data.","anchors":["FsF-R1.3-02D — F-UJI: 'Data is available in a file format recommended by the target research co","RDA-R1.3-02D — data is expressed in a machine-understandable community standard","RDA-I1-01D — data uses a knowledge representation expressed in a standardised format"],"scored":true,"signal":null},{"key":"i_community_standard_vocabulary","label":"Community standard / vocabulary","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No data or metadata community standard is named.","anchors":["RDA-R1.3-01M — 'Metadata complies with a community standard' (priority Essential)","RDA-R1.3-01D — 'Data complies with a community standard'","RDA-I2-01M — '(Meta)data use vocabularies that follow FAIR principles'"],"scored":false,"signal":null},{"key":"i_qualified_references","label":"Identifiers for the resources the data depend on","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No identifier for an external resource (e.g., another dataset, database, or code) is given.","anchors":["RDA-I3-01M — '(meta)data include references to other (meta)data'","RDA-I3-03M — 'metadata includes qualified references to other metadata'","FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":25.0,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No reuse license is named for the data; the CC-BY license applies to the article only.","anchors":["RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu","RDA-R1.1-02M — 'Metadata refers to a standard reuse licence'","RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'"],"scored":true,"signal":null},{"key":"r_provenance_methods","label":"Provenance of the data","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":"We manually collect data from the academic literature to construct a dataset of peptide self-assembly systems.","grounded":false,"rationale":"The data production is described in generic terms without naming specific instruments or kits. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (2/5 passes agreed)]","anchors":["RDA-R1.2-01M — 'Metadata includes provenance information according to community- specific standa","FsF-R1.2-01M — F-UJI: 'Metadata includes provenance information about data creation or generati","W3C PROV-O (W3C Recommendation, 2013) — the entity/activity/agent model of provenance"],"scored":false,"signal":null},{"key":"r_documentation_codebook","label":"Documentation / codebook","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"Example data entries in the database are shown in table S1.","grounded":true,"rationale":"The paper includes a supplementary table defining the data fields, but no documentation object (e.g., README) is named as traveling with the data.","anchors":["RDA-R1-01M — '(Meta)data are richly described with a plurality of accurate and relevant attribu","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'","NIH DMS Policy Element 3 (NOT-OD-21-014) — Standards (documentation and metadata to accompany t"],"scored":false,"signal":null},{"key":"r_versioning","label":"Snapshot identified","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"Neither a version token nor a date is provided for the data snapshot.","anchors":["DataCite Metadata Schema 4.6 — the 'Version' property","RDA-R1.2-01M — provenance information (which version was used is provenance)","NSTC Desirable Characteristics of Data Repositories (2022) — 'Provenance', 'Retention Policy'"],"scored":true,"signal":null},{"key":"x_code_availability","label":"Analysis code available","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"All data and codes are published online on Zenodo (DOI: 10.5281/zenodo.14791268).","grounded":false,"rationale":"A machine-resolvable locator (Zenodo DOI) is given for the code. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","anchors":["NIH DMS Policy Element 2 (NOT-OD-21-014) — 'Related Tools, Software and/or Code'","FAIR4RS Principles v1.0 (Chue Hong et al., 2022; RDA/FORCE11/ReSA) — FAIR Principles for Resear","FORCE11 Software Citation Principles (Smith, Katz & Niemeyer, 2016, PeerJ CS 2:e86)"],"scored":true,"signal":null},{"key":"x_funding_attribution","label":"Funder and award number","kind":"llm","weight":0.5,"fraction":1.0,"verdict":"yes","evidence":"US Department of Agriculture 2021-69012-35978","grounded":true,"rationale":"An award number is provided for a funder.","anchors":["DataCite Metadata Schema 4.6 — 'FundingReference' property (funderName, funderIdentifier, award","Crossref Funder Registry — canonical funder identifiers for funding metadata","RDA-F2-01M — rich metadata provided to allow discovery (funding is part of the descriptive reco"],"scored":true,"signal":null}]}},"actions":[{"key":"r_reuse_license","dimension":"R","label":"Reuse licence","action":"Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No reuse license is named for the data; the CC-BY license applies to the article only.","gain":16.67,"priority":"essential","scored":true},{"key":"a_data_openly_accessible","dimension":"A","label":"Access route free of preconditions","action":"Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For proteomics data, deposit in PRIDE (PXD accession) or ProteomeXchange.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All data and codes are published online on Zenodo (DOI: 10.5281/zenodo.14791268).","why":"The text gives a route to the data with no stated precondition. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","gain":8.33,"priority":"essential","scored":true},{"key":"f_dataset_cited","dimension":"F","label":"Dataset formally cited","action":"Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the proteomics repository accession (e.g. from PRIDE (PXD accession) or ProteomeXchange) in the reference list.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"All data and codes are published online on Zenodo (DOI: 10.5281/zenodo.14791268).","why":"The dataset's identifier appears only in the body text, not as a reference-list entry. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","gain":8.33,"priority":"important","scored":true},{"key":"i_open_nonproprietary_format","dimension":"I","label":"Open file format","action":"Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable. Prefer open proteomics formats such as mzML or mzIdentML.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No file format is named for the released data.","gain":8.33,"priority":"important","scored":true},{"key":"x_code_availability","dimension":"R","label":"Analysis code available","action":"Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI).","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All data and codes are published online on Zenodo (DOI: 10.5281/zenodo.14791268).","why":"A machine-resolvable locator (Zenodo DOI) is given for the code. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","gain":4.17,"priority":"important","scored":true},{"key":"r_versioning","dimension":"R","label":"Snapshot identified","action":"Version the deposit and cite the exact version analysed (a version-specific DOI, or an accession with its version suffix). A reader reproducing your work against 'the current release' is reproducing it against a different dataset.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"Neither a version token nor a date is provided for the data snapshot.","gain":4.17,"priority":"useful","scored":true},{"key":"f_data_availability_statement","dimension":"F","label":"Data-availability statement","action":"Replace the statement with the repository template: name the repository and give the accession or DOI (Colavizza category 3). This is the only DAS class associated with a measured citation advantage; 'available on reasonable request' and 'within the article' are not.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All data needed to evaluate the conclusions in this paper are present in the paper and/or the Supplementary Materials. All data and codes are published online on Zenodo (DOI: 10.5281/zenodo.14791268).","why":"The statement points to a repository record with a DOI (Colavizza category 3). [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","gain":0.0,"priority":"essential","scored":false},{"key":"a_access_conditions_stated","dimension":"A","label":"Access level labelled","action":"State the access level in words, using the standard vocabulary: 'These data are open access' / 'These data are controlled access'. A reader — and a harvester — should not have to infer the access level from the presence of a download link.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"All data and codes are published online on Zenodo (DOI: 10.5281/zenodo.14791268).","why":"The paper describes the action of publishing on Zenodo but does not explicitly label the access level (e.g., 'open access') for the data. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"i_community_standard_vocabulary","dimension":"I","label":"Community standard / vocabulary","action":"Adopt and NAME your domain's data standard — the minimum-information checklist, metadata schema, or ontology your community uses (MIAME/MINSEQE, ISA-Tab, BIDS, an OBO ontology, HL7 FHIR/OMOP) — and say which one you followed. A reporting checklist standardises your paper; it does nothing for your data. In proteomics, describe the data with mzML or MIAPE.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No data or metadata community standard is named.","gain":0.0,"priority":"important","scored":false},{"key":"r_provenance_methods","dimension":"R","label":"Provenance of the data","action":"Name the instruments, kits, and software — with versions — that produced the data, not just the verbs. 'Reads were aligned' is not provenance; 'aligned with STAR v2.7.9a to GRCh38' is, because someone else can rerun it.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"We manually collect data from the academic literature to construct a dataset of peptide self-assembly systems.","why":"The data production is described in generic terms without naming specific instruments or kits. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (2/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"r_documentation_codebook","dimension":"R","label":"Documentation / codebook","action":"Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. It is the cheapest single thing that makes a dataset usable by someone who was not in the lab, and a table buried in the article does not travel with the data.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"Example data entries in the database are shown in table S1.","why":"The paper includes a supplementary table defining the data fields, but no documentation object (e.g., README) is named as traveling with the data.","gain":0.0,"priority":"important","scored":false},{"key":"a_controlled_access_for_sensitive","dimension":"A","label":"Gatekeeper for sensitive data","action":"Route sensitive data through an institutional gatekeeper — deposit in a controlled- access repository (dbGaP, EGA) with a Data Access Committee and a published DUA — rather than through the corresponding author's inbox. An author-gated dataset dies with the author's email address, and 'on reasonable request' has been shown repeatedly not to yield data.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The data are not sensitive or human-subject, and no gatekeeper is named.","gain":0.0,"priority":"useful","scored":false},{"key":"i_qualified_references","dimension":"I","label":"Identifiers for the resources the data depend on","action":"Cite by identifier every resource the data depend on — the source datasets' accessions, the reference build (GRCh38 / GCA_000001405.28), the cohort application number, the code DOI — and register those relations on the dataset record (IsDerivedFrom, IsSupplementTo). A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No identifier for an external resource (e.g., another dataset, database, or code) is given.","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No sentence states when the data become available or how long they persist. [majority verdict 'no' (4/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For proteomics data, deposit in PRIDE (PXD accession) or ProteomeXchange.","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the proteomics repository accession (e.g. from PRIDE (PXD accession) or ProteomeXchange) in the reference list.","Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable. Prefer open proteomics formats such as mzML or mzIdentML.","Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI)."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-07-20T11:53:45.262920Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}