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Cited by 160Computational Drug Discovery MethodsBioinformatics and Genomic NetworksBiomedical Text Mining and Ontologies

TCRD and pharos 2021: mining the human proteome for disease biology

Open access
Sheils, Timothy K, Mathias, Stephen L, Kelleher, Keith J, Siramshetty, Vishal B, Nguyen, Dac-Trung, Bologa, Cristian G, Jensen, Lars Juhl, Vidović, Dušica +11 more·2021·Nucleic Acids Research
DOI 10.1093/nar/gkaa993PMC PMC7778974
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Abstract

In 2014, the National Institutes of Health (NIH) initiated the Illuminating the Druggable Genome (IDG) program to identify and improve our understanding of poorly characterized proteins that can potentially be modulated using small molecules or biologics. Two resources produced from these efforts are: The Target Central Resource Database (TCRD) (http://juniper.health.unm.edu/tcrd/) and Pharos (https://pharos.nih.gov/), a web interface to browse the TCRD. The ultimate goal of these resources is to highlight and facilitate research into currently understudied proteins, by aggregating a multitude of data sources, and ranking targets based on the amount of data available, and presenting data in machine learning ready format. Since the 2017 release, both TCRD and Pharos have produced two major releases, which have incorporated or expanded an additional 25 data sources. Recently incorporated data types include human and viral-human protein–protein interactions, protein–disease and protein–phenotype associations, and drug-induced gene signatures, among others. These aggregated data have enabled us to generate new visualizations and content sections in Pharos, in order to empower users to find new areas of study in the druggable genome.

AI snapshot

Written from the paper’s full text.

TL;DR

TCRD and Pharos 2021 describe an update to the Target Central Resource Database and its web interface, which aggregate human proteome data to illuminate understudied and potentially druggable targets. The latest TCRD v6.7 integrates 78 data sources, and Pharos adds new visualizations, GraphQL search, and expanded disease, ligand, expression, and interaction views.

Key findings

  • The latest TCRD version 6.7 aggregates data from 78 data sources; since the 2017 release, two major releases incorporated or expanded an additional 25 data sources. New data types include human and viral-human protein–protein interactions, protein–disease and protein–phenotype associations, and drug-induced gene signatures.
  • Target development levels (TDLs) currently include 659 human proteins as Tclin, 1607 as Tchem, and approximately 31% of manually curated human proteins in UniProt as Tdark. Figure 1 shows a decrease in Tdark and an increase in other development levels between TCRD v3.0 and v6.7.
  • As of 3 September 2020, Pharos had been cited more than 110 times, was accessed by approximately 1600 new visitors monthly, had about 425 000 pageviews, and had more than 20 000 full TCRD database downloads.
  • Pharos features added or improved include a TDL description panel, interactive sex-specific anatomograms, a 3D PDB viewer using NGL Viewer, predicted viral-human interactions from P-HIPSTer, expanded disease pages with TIN-X, ligand detail pages, improved browse filters, and custom target lists.

Methods

  • This is a database and web-resource update. TCRD collates data from 78 sources and is based on reviewed human protein entries from UniProt; Pharos serves as the web interface. Integrated data include expression data from GTEx, Human Protein Atlas, TISSUES, and others; PPI data from STRING 11, BioPlex, and Reactome; disease and phenotype ontologies; and drug/ligand sources.
  • TDLs were recalculated using automated scripts when target criteria changed. TDL categories are Tclin, Tchem, Tbio, and Tdark, with criteria based on approved drug targets, high-potency small-molecule binding, Gene Ontology leaf annotations, publication counts, Gene RIF annotations, or commercial antibodies.
  • Pharos was redesigned based on user feedback and interviews, switched from a REST API to a GraphQL instance, and moved to a hybrid client/server application. GraphQL benchmarking is summarized in Supplementary Table S1.

Limitations

  • The paper does not present a formal limitations section. It states that ongoing work focuses on using AI/ML-ready data to prioritize dark targets and on evaluating ways to aggregate experimental data uncertainties, specifically data quality and reliability.
  • Evident from the text: several integrated sources overlap in data and content, though they may also present unique data, and text-mining-based resources tend to be updated more often than experimental databases. No formal user evaluation or accuracy metrics are reported in the main text; GraphQL benchmarking is only noted as being in the supplement.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1093/nar/gkaa993

Cites

53 of 53 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 36 cited sources checked · 0 supported · 0 flagged

  • Findingnone given

    Since the 2017 release, both TCRD and Pharos have produced two major releases, which have incorporated or expanded an additional 25 data sources.

    “Since the 2017 release, both TCRD and Pharos have produced two major releases, which have incorporated or expanded an additional 25 data sources.”
    Quote in the paperNot a substantial claim
  • Findingnone given

    The scope of TCRD has been expanded to aggregate data about the entire human proteome.

    “The scope of TCRD has also been expanded, moving past the initial area of focus of the druggable genome to aggregate data about the entire human proteome.”
    Quote in the paperSubstantial claim
  • Findingcitation

    Target expression data was primarily extracted from GTEx, the Human Protein Atlas, UniProt and TISSUES.

    “Target expression data was primarily extracted from GTEx (12), the Human Protein Atlas (HPA) (13), UniProt and TISSUES (14).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [12] Consortium, GTEx, 2020, The GTEx Consortium atlas of genetic regulatory effects across human tissues, Science source

      Not checked in the free run.

    • cites [13] Thul, 2018, The human protein atlas: a spatial map of the human proteome, Protein Sci. source

      Not checked in the free run.

    • cites [14] Palasca, 2018, TISSUES 2.0: an integrative web resource on mammalian tissue expression, Database source

      Not checked in the free run.

  • Findingreasoning

    The Disease Ontology data were further extended and newer ontologies such as Rat Disease Ontology and Mammalian Phenotype Ontology were added to facilitate comparison of target-disease and target-phenotype associations across multiple species.

    “The Disease Ontology (DO) (8) data were further extended and newer ontologies such as Rat Disease Ontology (9) and Mammalian Phenotype Ontology (10) were added to facilitate comparison of target-disease and target-phenotype associations across multiple species.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [8] Schriml, 2012, Disease Ontology: a backbone for disease semantic integration, Nucleic Acids Res. source

      Not checked in the free run.

    • cites [9] Hayman, 2016, The Disease Portals, disease-gene annotation and the RGD disease ontology at the Rat Genome Database, Database source

      Not checked in the free run.

    • cites [10] Smith, 2009, The mammalian phenotype ontology: enabling robust annotation and comparative analysis, Wiley Interdiscip. Rev. Syst. Biol. Med. source

      Not checked in the free run.

  • Findingown data

    The decrease of Tdark and subsequent increase of other development levels shows an overall increase in target illumination.

    “The decrease of Tdark and subsequent increase of other development levels shows an overall increase in target illumination.”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim. 65
  • May combine two claims. 32

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Since its initial launch, the Pharos paper was cited more than 110 times.

    “Since its initial launch, the Pharos paper was cited in more than 110 times cf. Google Scholar”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    As of 3 September 2020, the Pharos portal had an average of ∼1600 new visitors monthly, a total of ∼425 000 pageviews, and >20 000 full TCRD database downloads.

    “the portal is accessed on average by ∼1600 new visitors monthly, with a total of ∼ 425 000 pageviews and >20 000 full TCRD database downloads (as of 3 September 2020).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    TCRD has been enhanced by inclusion of new data types and data from emerging resources, which were prepared for machine-learning readiness.

    “TCRD has been enhanced by inclusion of new data types and data from emerging resources, which were prepared for machine-learning readiness.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    The search functionality on the Pharos web server has been upgraded to use the GraphQL API, which facilitates faster data retrieval directly from TCRD.

    “the search functionality on the Pharos web server has been upgraded to use the graph querying language (GraphQL; https://graphql.org/) API that facilitates faster data retrieval, directly from TCRD.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    The newly added data includes mouse and rat proteins from UniProt, with their associated phenotype data extracted from the International Mouse Phenotyping Consortium and the Rat Genome Database.

    “The newly added data includes mouse and rat proteins from UniProt (5), with their associated phenotype data extracted from the International Mouse Phenotyping Consortium (6) and the Rat Genome Database (7), respectively.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [5] Consortium, 2019, UniProt: a worldwide hub of protein knowledge, Nucleic Acids Res. source

      Not checked in the free run.

    • cites [6] Dickinson, 2016, High-throughput discovery of novel developmental phenotypes, Nature source

      Not checked in the free run.

    • cites [7] Smith, 2020, The Year of the Rat: The Rat Genome Database at 20: a multi-species knowledgebase and analysis platform, Nucleic Acids Res.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    The latest version of Pharos uses TCRD version 6.7, which currently aggregates data from 78 data sources.

    “the latest version uses TCRD version 6.7, which currently aggregates data from 78 data sources (see Supplementary Information).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingnone given

    Recently incorporated data types include human and viral-human protein-protein interactions, protein-disease and protein-phenotype associations, and drug-induced gene signatures, among others.

    “Recently incorporated data types include human and viral-human protein–protein interactions, protein–disease and protein–phenotype associations, and drug-induced gene signatures, among others.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    TCRD is based on 'reviewed' (manually curated) human protein entries from UniProt.

    “However, TCRD is based on ‘reviewed’ (manually curated) human protein entries from UniProt.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    The GTEx dataset was further extended to include sex-specific expression values.

    “The GTEx dataset was further extended to include sex-specific expression values.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingcitation

    Additional data was included from GWAS and OMIM resources.

    “Similarly, additional data was included from GWAS (11) and OMIM (https://omim.org/) resources.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [11] Buniello, 2019, The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019, Nucleic Acids Res. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingcitation

    Cell line expression data was added from HPA and the Human Proteome Map, and expression data was collected for orthologous genes from 17 different species.

    “In addition, cell line expression data was added from HPA and the Human Proteome Map (15) and expression data was collected for orthologous genes from 17 different species.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [15] Kim, 2014, A draft map of the human proteome, Nature source

      Not checked in the free run.

  • May combine two claims.

    Findingcitation

    Other expression datasets integrated into the latest version are the Cancer Cell Line Encyclopedia and cell perturbation expression data from the Library of Integrated Network-Based Cellular Signatures.

    “Other expression datasets integrated into the latest version are the Cancer Cell Line Encyclopedia (16) and cell perturbation expression data from the Library of Integrated Network-Based Cellular Signatures (17).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [16] Barretina, 2012, The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity, Nature source

      Not checked in the free run.

    • cites [17] Stathias, 2020, LINCS Data Portal 2.0: next generation access point for perturbation-response signatures, Nucleic Acids Res. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingcitation

    The target expression panel was visually upgraded with interactive anatomograms for both sexes, which further provides systematic mappings to the source tissues.

    “Furthermore, the target expression panel was visually upgraded with interactive anatomograms (18) (https://www.ebi.ac.uk/gxa) for both sexes which further provides systematic mappings to the source tissues.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [18] Papatheodorou, 2020, Expression Atlas update: from tissues to single cells, Nucleic Acids Res.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingcitation

    Tclin are protein drug targets via which approved drugs act, and currently include 659 human proteins.

    “Tclin are protein drug targets via which approved drugs act (24–26), which currently includes 659 human proteins”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [24] Santos, 2017, A comprehensive map of molecular drug targets, Nat. Rev. Drug Discov. source

      Not checked in the free run.

    • cites [25] Ursu, 2019, Novel drug targets in 2018, Nat. Rev. Drug Discov.

      Not checked in the free run.

    • cites [26] Avram, 2020, Novel drug targets in 2019, Nat. Rev. Drug Discov. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    Many tables were swapped with sortable list elements, allowing more data to be shown than a table would allow and also allowing dynamic data display.

    “Many tables were swapped with sortable list elements, akin to a shopping site, allowing more data to be shown than a table would allow and also allowing us to display dynamic data as desired.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    Sub-lists are generated on entity pages that can be viewed in their respective list browsers.

    “In addition, sub-lists are generated on entity (target/disease/ligand) pages that can be viewed in their respective list browsers.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingreasoning

    The target development levels for respective targets were recalculated when the target criteria changed, using automated scripts.

    “As the amount of data available for each target changed with each release of TCRD, the target development levels (TDLs) for respective targets were recalculated when the target criteria changed. This was done using automated scripts.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    For numeric values, a range slider allows users to refine results.

    “In the case of numeric values, such as novelty and PubMed score, a range slider allows users to refine results.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    In the first 2 years following the initial release, the Pharos team frequently demoed the site, with a focus on obtaining user feedback, which provided the user-centered design information needed as Pharos underwent a ground-up rewrite in late 2018.

    “In the first 2 years following the initial release, the Pharos team frequently demoed the site, with a focus on obtaining user feedback, which provided the user-centered design information needed as Pharos underwent a ground-up rewrite in late 2018.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    All filters have a '?' help button that allows users to view a quick definition of the filter or to visit the original source.

    “All filters also have a ‘?’ help button that allows users to view a quick definition of the filter or to visit the original source, if desired.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    Filter functionality has been expanded, and users are able to examine the entire list of values for each filter, as well as search for text within the filter values.

    “Filter functionality has been expanded, and users are able to examine the entire list of values for each filter, as well as search for text within the filter values.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    Pharos is installable as a Progressive Web App, which allows users to install Pharos as a mobile application on their device, increasing ease of access.

    “Pharos is also installable as a Progressive Web App, which allows users to install Pharos as a mobile application on their device, increasing the ease of access for Pharos.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    Pharos was redesigned with a focus on mobile usability, adjusting styles and visualizations depending on the screen used.

    “Pharos was also redesigned with a focus on mobile usability, adjusting styles and visualizations depending on the screen used.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingreasoning

    By focusing on user needs, the team was able to streamline target presentation and simplify many pages.

    “By focusing on user needs, such as improving the target details page hierarchy and navigation, and adding more detailed explanations of the terms and ideas represented within Pharos, we were able to streamline target presentation, and simplify many pages.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    Tchem are proteins that are not Tclin but are known to bind small molecules with high potency, currently N = 1607.

    “Tchem are proteins that are not Tclin, but are known to bind small molecules with high potency (currently N = 1607)”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    By registering, users are able to select targets of interest and save them as custom lists, which are added to the main filter panel and are always available.

    “By registering, users are able to select targets of interest and save them as custom lists, which are added to the main filter panel, and are always available.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    Drug and ligand browsing is now done via a pageable list.

    “Drug and ligand browsing is now done via a pageable list.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    The disease associations panel has been greatly expanded, incorporating DisGeNet and eRAM, as well as in size and placement.

    “The disease associations panel has been greatly expanded, both in the amount of featured resources, now incorporating DisGeNet (31) and eRAM (32), as well as in size and placement.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [31] Piñero, 2020, The DisGeNET knowledge platform for disease genomics: 2019 update, Nucleic Acids Res.

      Not checked in the free run.

    • cites [32] Jia, 2018, eRAM: encyclopedia of rare disease annotations for precision medicine, Nucleic Acids Res. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    Predicted viral-human protein interactions from the P-HIPSTer atlas are displayed in a separate panel that shows a list of viruses and their associated taxonomic data, specifically for the targeted human protein.

    “Predicted viral-human protein interactions from the P-HIPSTer atlas are displayed in a separate panel that shows a list of viruses and their associated taxonomic data, specifically for the targeted human protein.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    The source of each disease association is displayed as a collapsible panel that bundles multiple sources for the same disease.

    “The source of each disease association is displayed as a collapsible panel that bundles multiple sources for the same disease.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    Sections where no data are available, such as drug and ligand browsers for Tdark and Tbio targets, are automatically removed.

    “Sections where no data are available, such as drug and ligand browsers for Tdark and Tbio targets, are automatically removed.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingcitation

    The target expression data panel was expanded by replacing the static human figure with an expanded, interactive anatomogram.

    “The target expression data panel has also been expanded, as shown in Figure 6. We replaced the static human figure with an expanded, interactive anatomogram (18).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [18] Papatheodorou, 2020, Expression Atlas update: from tissues to single cells, Nucleic Acids Res.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingcitation

    The 3D visualization employs NGL Viewer and is highly interactive, allowing users to drag, zoom, pan and spin the structure to thoroughly examine it.

    “This 3D visualization, employing NGL Viewer (34,35), is highly interactive, allowing users to drag, zoom, pan and spin the structure to thoroughly examine it.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [34] Rose, 2018, NGL viewer: web-based molecular graphics for large complexes, Bioinformatics source

      Not checked in the free run.

    • cites [35] Rose, 2015, NGL Viewer: a web application for molecular visualization, Nucleic Acids Res. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    Where data or reagents are available from IDG Consortium members, a browseable section is displayed in Pharos, allowing users to navigate to the data set and even order them in the case of physical resources.

    “Where data or reagents are available, a browseable section is displayed in Pharos, allowing users to navigate to the data set, and even order them in the case of physical resources”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    The navigation panel is always visible on the left hand side, allowing users to easily jump to the section of interest.

    “The navigation panel is always visible on the left hand side, allowing users to easily jump to the section of interest.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    Most data panels have been improved by adding tooltips to further explain properties, and a help panel that contains additional information such as definitions, explanatory articles or raw data.

    “Most data panels have been improved by adding tooltips to further explain properties, and a help panel that contains additional information, such as definitions, explanatory articles or raw data.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    The ligand details page shows a 2D depiction of the ligand chemical structure, together with synonyms and identifiers from PubChem, Guide to Pharmacology, ChEMBL and DrugCentral.

    “A 2D depiction of the ligand chemical structure is shown, together with synonyms and identifiers from PubChem (43), Guide to Pharmacology (44), ChEMBL and DrugCentral.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [43] Kim, 2019, PubChem 2019 update: improved access to chemical data, Nucleic Acids Res. source

      Not checked in the free run.

    • cites [44] Armstrong, 2020, The IUPHAR/BPS guide to Pharmacology in 2020: extending immunopharmacology content and introducing the IUPHAR/MMV guide to Malaria Pharmacology, Nucleic Acids Res.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    The PPI list displays the illumination graph, the originating data source, and the confidence of the interaction.

    “These targets display the illumination graph, which gives users a quick visual representation of the level and types of knowledge available for the target. The originating data source is also displayed, as well as the confidence of this interaction.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    In the finding experimental tools use case, the target details page for KCNS2 lists three approved drugs (e.g. amifampridine) which are known to block this channel.

    “The target details page for KCNS2 lists three approved drugs (e.g. amifampridine) which are known to block this channel.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    In the binding partner search use case, selecting Tclin filters the list to 10 potential binding partners that have approved drugs.

    “Selecting Tclin, she filters the list to 10 potential binding partners that have approved drugs, with new therapeutic effects and drug-related side effects that can assist in her research.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    The PPI panel consists of a pageable list of targets known to interact with the current target.

    “This panel consists of a pageable list of targets known to interact with the current target.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    In the TIN-X disease plot, the X-axis shows the Novelty of the target-disease relationship, and the Y-axis shows the Importance of that target to the disease, both on a log10 scale.

    “The X-axis shows the Novelty of the target-disease relationship, while the Y-axis shows the Importance of that target to the disease, both on a log10 scale.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    On the ligand details page, activity type, value and mechanism of action are shown, in addition to reference publication for each activity, allowing users to directly view the source.

    “Activity type, value and mechanism of action are shown, in addition to reference publication for each activity, allowing users to directly view the source.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    Text-mining-based resources tend to be updated more often than frequently accessed scientific databases that aggregate experimental data.

    “It also illustrates that the text-mining-based resources tend to be updated more often than frequently accessed scientific databases that aggregate experimental data.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    In the asthma use case, filtering the 470 targets with data from the Expression Atlas yields 78 targets.

    “Filtering those with data from the Expression Atlas (18), using the ‘Expression Atlas’ value from the ‘Disease Data Source’ filter, yields 78 targets”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [18] Papatheodorou, 2020, Expression Atlas update: from tissues to single cells, Nucleic Acids Res.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    One area that received significant attention in the current update is the search mechanism, which was upgraded with the implementation of GraphQL API.

    “One area that received significant attention in the current update is the search mechanism which was upgraded with the implementation of GraphQL API.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingreasoning

    The TIN-X disease view is a scatterplot of novel targets related to the disease of interest.

    “Similar to the target based TIN-X view, this is a scatterplot of novel targets related to the disease of interest.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    The anatomogram visualization contains both male and female figures, allowing sex-specific tissue information to be highlighted.

    “This visualization contains both male and female figures, allowing sex-specific tissue information (e.g., from GTEx) to be highlighted.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingcitation

    When possible, all source tissues have been mapped to standardized Uberon identifiers, enabling merging of repetitive tissues.

    “When possible, all source tissues have been mapped to standardized Uberon (38) identifiers, enabling us to merge repetitive tissues.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [38] Mungall, 2012, Uberon, an integrative multi-species anatomy ontology, Genome Biol. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    On the disease details page, help definition buttons are shown for each section of data when available.

    “When available, help definition buttons are also shown for each section of data.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    The introduction of data from Bioplex, STRING and Reactome has allowed display of rich PPI data and allows users to examine how multiple targets may interact.

    “The introduction of data from Bioplex (39), STRING and Reactome (40) has allowed us to display rich PPI data, and allows users to examine how multiple targets may interact”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [39] Huttlin, 2020, Dual proteome-scale networks reveal cell-specific remodeling of the human interactome source

      Not checked in the free run.

    • cites [40] Jassal, 2020, The reactome pathway knowledgebase, Nucleic Acids Res.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    Pharos 3.0 expands on the data collected and displayed about diseases.

    “Pharos 3.0 expands on the data collected and displayed about diseases.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    On the ligand details page, activity values are displayed in collapsible panels and sorted by target.

    “Activity values are displayed in collapsible panels, and sorted by target.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    For lists of associated targets, an additional column has been added to the target card, showing disease association details, such as the evidence associated with a given data source.

    “Also of note, for lists of associated targets, an additional column has been added to the target card, showing disease association details, such as the evidence associated with a given data source.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    In the target list search use case, filtering to targets listed by the IDG Consortium as targets of interest, in the ion channel family, with a nervous system phenotype as described by the Mouse Phenotype Ontology from the Jackson Laboratory yields 16 potential targets of interest.

    “Filtering to targets listed by the IDG Consortium as targets of interest (https://druggablegenome.net/IDGProteinList), in the ion channel family, with a nervous system phenotype as described by the Mouse Phenotype Ontology from the Jackson Laboratory yields 16 potential targets of interest.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    On the disease details page, a description from the Disease Ontology is shown when available.

    “When available, a description from the Disease Ontology is shown.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingcitation

    The target-disease Novelty score is shown in the TIN-X panel on the disease details page.

    “The target-disease Novelty score is shown in the Target-Importance Novelty eXplorer (TIN-X, (41) panel.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [41] Cannon, 2017, TIN-X: target importance and novelty explorer, Bioinformatics source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    The ligand details page has been expanded to include a description of the ligand, where available.

    “The ligand details page has been expanded to include a description of the ligand, where available.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    The disease details page shows the hierarchy of each specific disease, allowing users to view parent or child diseases or syndromes, as well as siblings.

    “The hierarchy of each specific disease is also shown, allowing users to view parent or child diseases or syndromes, as well as the siblings for each disease.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    In the finding experimental tools use case, the IDG Resources show a cell line and a mouse genetic construct, which can be ordered from the IDG Consortium (UCSF, in this case).

    “The IDG Resources show a cell line and a mouse genetic construct, which can be ordered from the IDG Consortium (UCSF, in this case).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    In the disease-based search use case, starting from the Asthma disease details page and clicking 'Explore Associated Targets' shows 470 potential targets.

    “Starting from the Asthma disease details page, he clicks ‘Explore Associated Targets’ to see 470 potential targets.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    On the ligand details page, clicking on a target header allows users to examine activity values for that ligand on the selected target.

    “By clicking on a target header, users are able to examine activity values for that ligand on the selected target.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    The disease details page shows a breakdown of the targets associated with each disease, which can be opened in the target browse page to filter the list of associated targets.

    “In addition, a breakdown of the targets associated with each disease is shown, which can also be opened in the target browse page, allowing users to filter the list of associated targets.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    Most of the above described developments are based on the feedback obtained directly from the website visitors, several demo sessions and presentations at scientific meetings.

    “Most of the above described developments are based on the feedback obtained directly from the website visitors, several demo sessions and presentations at scientific meetings.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    Most data that have been recently integrated into TCRD facilitate application of AI/ML techniques for target evaluation and drug repositioning, and are accessible in ML ready format.

    “Further, most data that have been recently integrated into TCRD facilitate application of artificial intelligence/machine learning (AI/ML) techniques for target evaluation and drug repositioning (47), and are accessible in ML ready format.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [47] Levin, 2020, Artificial intelligence, drug repurposing and peer review, Nat. Biotechnol. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    The TDL descriptions panel and the target expression anatomograms are the significantly improved components of the Pharos web interface.

    “The TDL descriptions panel and the target expression anatomograms are the significantly improved components of the Pharos web interface.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    To improve user interaction with the new API, example queries have been made available on the website.

    “To improve user interaction with the new API, example queries have been made available on the website.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationnone given

    Replacing the REST API with a GraphQL instance adds flexibility to data retrieval and potentially reduces the amount of data sent over the network.

    “We replaced the REST API with a GraphQL instance, which adds flexibility to data retrieval, as well as potentially reducing the amount of data being sent over the network.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The TDL description panel provides valuable evidence that illustrates to the user how TCRD generated the ranking.

    “This provides valuable evidence that illustrates to the user how TCRD generated this ranking.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    ACE2 is the functional entry receptor for both SARS-CoV and SARS-CoV-2.

    “ACE2 is the functional entry receptor for both severe acute respiratory syndrome (SARS) coronaviruses, SARS-CoV (36) and SARS-CoV-2 (37).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [36] Li, 2003, Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus, Nature source

      Not checked in the free run.

    • cites [37] Hoffmann, 2020, SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor, Cell source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    With the newly added data, interactive visualizations and enhanced search capabilities, TCRD and Pharos in their current forms serve as IDG resources that facilitate better exploration of the dark and understudied regions of the human genome.

    “With the newly added data, interactive visualizations and enhanced search capabilities, TCRD and Pharos in their current forms serve as IDG resources that facilitate better exploration of the dark and understudied regions of the human genome.”
    Quote in the paperSubstantial claim
71 of 71

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The current version of DrugCentral reports 708 Tchem, 415 Tbio and 26 Tdark proteins, mapped onto TCRD and interfaced with Pharos.

    “The current version of DrugCentral reports 708 Tchem, 415 Tbio and 26 Tdark proteins, mapped onto the Target Central Resource Database (TCRD) and interfaced with the TCRD portal, Pharos, respectively (39,40).”

    From DrugCentral 2023 extends human clinical data and integrates veterinary drugs (2023) · cites this paper as [40]

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Authors
Sheils, T. K., Mathias, S. L., Kelleher, K. J., Siramshetty, V. B., Nguyen, D.-T., Bologa, C. G., Jensen, L. J., Vidović, D., Koleti, A., Schürer, S. C., Waller, A., Yang, J. J., Holmes, J., Bocci, G., Southall, N., Dharkar, P., Mathé, E., Simeonov, A., & Oprea, T. I.
Affiliations
  • National Center for Advancing Translational Sciences (US)
  • University of New Mexico (US)
  • National Center for Advancing Translational Science, 9800 Medical Center Drive, Rockville, MD 20850, USA
  • University of Copenhagen (DK)
  • University of Miami (US)
  • University of New Mexico Health Sciences Center (US)
Corresponding author
Oprea, Tudor I
ORCID
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2020-11-06
Volume
49
Issue
D1
Pages
D1334-D1346
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
DOI
10.1093/nar/gkaa993
PMC
PMC7778974
OpenAlex
W3094762523
Semantic Scholar
8d2310e3a67d3344f7592fa304ee163435ecbcf1
Cited by
160
References
53
Citations by year
2026: 17 · 2025: 18 · 2024: 27 · 2023: 43 · 2022: 35 · 2021: 19 · 2020: 1
FWCI
12.17
Type
journal article
Language
en
Open access
Licence
Locations
  • Nucleic Acids Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
Funders
  • National Institutes of Health (CA224370, U24TR002278)
  • Novo Nordisk Foundation (NNF14CC0001)
  • Intramural Research Program, Division of Preclinical Innovation, NIH NCATS
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
Keywords
Pharo, druggable genome, human proteome, drug target prioritization, protein-protein interaction, data aggregation
MeSH terms
Machine Learning, Animals, Anticonvulsants, Antiviral Agents, Biological Products, Humans, Software, Virus Diseases, Genome, Human, Databases, Factual, Mice, Knockout, Neurodegenerative Diseases, Internet, Proteome, Protein Interaction Mapping, Proteomics, Mice, Small Molecule Libraries, Host-Pathogen Interactions, Data Mining, Molecular Targeted Therapy

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.

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