Machine learning prediction and tau-based screening identifies potential Alzheimer’s disease genes relevant to immunity is a dataset published in Communications Biology (2022). On theSindex it has a DataRank of 1.4, placing it in the top 14.6% of the data-sharing corpus. It has been cited 52 times, with 43 citing works in its 1-hop citation network. Its calibrated FAIR score is 23/100.
Ranks in the top 15% for downstream scientific impact
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Full FAIR picture · advisory
The headline score is computed from the scored criteria — the fact-shaped checks (a repository, an accession, a licence) that two independent models agree on. The advisory criteria below are real FAIR guidance but rest on judgment calls that models read differently, so they inform without moving the number.
“Data used for analysis in this study and raw images are available at https://figshare.com/projects/Machine_learning_prediction_and_tau-based_screening_identifies_potential_Alzheimer_s_disease_genes_relevant_to_immunity/127145.”— not found in the paper; verdict downgraded
The identifier is a figshare project URL, which is not a PID scheme (DOI, Handle, ARK, etc.). [downgraded to 'no' — no verifiable quote from the paper]
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'
“Data used for analysis in this study and raw images are available at https://figshare.com/projects/Machine_learning_prediction_and_tau-based_screening_identifies_potential_Alzheimer_s_disease_genes_relevant_to_immunity/127145.”— not found in the paper; verdict downgraded
Figshare is a named repository that issues accessions and commits to retention. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]
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
“Data used for analysis in this study and raw images are available at https://figshare.com/projects/Machine_learning_prediction_and_tau-based_screening_identifies_potential_Alzheimer_s_disease_genes_relevant_to_immunity/127145.”— not found in the paper; verdict downgraded
The dataset identifier (figshare URL) appears only in the body text, not in the reference list. [downgraded to 'no' — no verifiable quote from the paper]
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'
Advisory · not in the published score
“Data used for analysis in this study and raw images are available at https://figshare.com/projects/Machine_learning_prediction_and_tau-based_screening_identifies_potential_Alzheimer_s_disease_genes_relevant_to_immunity/127145.”— not found in the paper; verdict downgraded
The statement points to a repository (figshare) with a persistent link, fitting Colavizza category 3. [downgraded to 'partial' — no verifiable quote from the paper]
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
“Data used for analysis in this study and raw images are available at https://figshare.com/projects/Machine_learning_prediction_and_tau-based_screening_identifies_potential_Alzheimer_s_disease_genes_relevant_to_immunity/127145.”— not found in the paper; verdict downgraded
The dataset's content and extent are described in a single sentence, not in an itemised inventory. [downgraded to 'no' — no verifiable quote from the paper]
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'
“Data used for analysis in this study and raw images are available at https://figshare.com/projects/Machine_learning_prediction_and_tau-based_screening_identifies_potential_Alzheimer_s_disease_genes_relevant_to_immunity/127145.”— not found in the paper; verdict downgraded
The figshare link is given with no stated precondition, indicating unconditional availability. [downgraded to 'partial' — no verifiable quote from the paper]
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'
Advisory · not in the published score
“Data used for analysis in this study and raw images are available at https://figshare.com/projects/Machine_learning_prediction_and_tau-based_screening_identifies_potential_Alzheimer_s_disease_genes_relevant_to_immunity/127145.”— not found in the paper; verdict downgraded
The sentence describes the action of where the data can be accessed but does not use an explicit access-level label from the standard vocabulary. [downgraded to 'no' — no verifiable quote from the paper]
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
“Data used for analysis in this study and raw images are available at https://figshare.com/projects/Machine_learning_prediction_and_tau-based_screening_identifies_potential_Alzheimer_s_disease_genes_relevant_to_immunity/127145.”— not found in the paper; verdict downgraded
The deposited data are openly accessible at a public repository with no gatekeeper mentioned; the human tissue data are not subject to controlled access according to the statement. [majority verdict 'no' (4/5 passes agreed)]
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
No sentence in the paper states how long the data will remain available or a retention commitment.
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'
No file format is named for the released data.
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
Advisory · not in the published score
No data or metadata community standard is named in the paper.
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'
“For full analysis are at https://doi.org/10.5281/zenodo.5784581.”— not found in the paper; verdict downgraded
The paper provides a Zenodo DOI for the code, which is a resource other than the own dataset. [downgraded to 'no' — no verifiable quote from the paper]
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'
No license is stated for the dataset; the article's CC BY license applies to the paper, not the data.
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'
No version token or date is given for the study's own data snapshot.
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'
“The ProteinGraphML software is available at https://github.com/unmtransinfo/ProteinGraphML. For full analysis are at https://doi.org/10.5281/zenodo.5784581.”— not found in the paper; verdict downgraded
Machine-resolvable locators (GitHub repository and Zenodo DOI) are provided for the code. [downgraded to 'partial' — no verifiable quote from the paper]
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)
“This work was primarily funded by the NIH Common Fund U24 CA224370-01S1 AD/ADRD supplement.”— not found in the paper; verdict downgraded
A specific grant number (U24 CA224370-01S1) is attached to the funder. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]
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
Advisory · not in the published score
“For machine learning, we selected XGBoost 38, an ML algorithm more rigorous than LightGBM.”— not found in the paper; verdict downgraded
The paper names a specific tool (XGBoost) used to produce the data. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]
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
No documentation object (README, data dictionary, codebook) is mentioned as accompanying the data. [majority verdict 'no' (4/5 passes agreed)]
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
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
Base Score Contribution
0.596
From this paper's citation signal
Citation Network Contribution
0.816
From 37 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 43 citers.
NIGMS NIH HHS
Grant: K12 GM088021
NIGMS NIH HHS
Grant: P20 GM121176
NCI NIH HHS
Grant: U24 CA224370
NINDS NIH HHS
Grant: R21 NS093442
NCATS NIH HHS
Grant: U24 TR002278
NINDS NIH HHS
Grant: RF1 NS083704
NINDS NIH HHS
Grant: R01 NS083704
NINDS NIH HHS
Grant: R21 NS077089
NIA NIH HHS
Grant: P30 AG013854
National Institutes of Health
Grant: 5P30AG013854-05
CORE--CLINICAL
National Institutes of Health
Grant: 5U24CA224370-06
Knowledge Management Center for Illuminating the Druggable Genome
National Institutes of Health
Grant: 3R01NS083704-04S1
The role of inflammasome signaling in tauopathies
National Institutes of Health
Grant: 7R21NS077089-02
The role of microglial-and neuron-specific MyD88 signaling in tauopathies
National Institutes of Health
Grant: 1R21NS093442-01A1
Light-based regulation of autophagy processing to target pathological forms of tau
National Institutes of Health
Grant: 1U24TR002278-01
Illuminating the Druggable Genome Resource Dissemination and Outreach Center (IDG-RDOC)
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Machine learning assists prediction of genes responsible for plant specialized metabolite biosynthesis by integrating multi-omics data
Additional file 1 of Machine learning assists prediction of genes responsible for plant specialized metabolite biosynthesis by integrating multi-omics data
Additional file 2 of Machine learning assists prediction of genes responsible for plant specialized metabolite biosynthesis by integrating multi-omics data
Additional file 2 of Machine learning assists prediction of genes responsible for plant specialized metabolite biosynthesis by integrating multi-omics data