DisMaNET: A network-based tool to cross map disease vocabularies

García Del Valle, Eduardo Pantaleón and Lagunes García, Gerardo and Prieto Santamaria, Lucia and Zanin Zanin, Massimiliano and Menasalvas Ruiz, Ernestina and Rodríguez González, Alejandro (2021). DisMaNET: A network-based tool to cross map disease vocabularies. "Computer Methods And Programs in Biomedicine", v. 207 ; pp. 1-22. ISSN 0169-2607. https://doi.org/10.1016/j.cmpb.2021.106233.


Title: DisMaNET: A network-based tool to cross map disease vocabularies
  • García Del Valle, Eduardo Pantaleón
  • Lagunes García, Gerardo
  • Prieto Santamaria, Lucia
  • Zanin Zanin, Massimiliano
  • Menasalvas Ruiz, Ernestina
  • Rodríguez González, Alejandro
Item Type: Article
Título de Revista/Publicación: Computer Methods And Programs in Biomedicine
Date: 2021
ISSN: 0169-2607
Volume: 207
Freetext Keywords: Disease vocabularies, Data interoperability, Disease cross-mapping, Graph database, Network analysis
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Background and Objectives The growing integration of healthcare sources is improving our understanding of diseases. Crossmapping resources such as UMLS play a very important role in this area, but their coverage is still incomplete. With the aim to facilitate the integration and interoperability of biological, clinical and literary sources in studies of diseases, we built DisMaNET, a system to cross-map terms from disease vocabularies by leveraging the power and intuitiveness of network analysis. Methods First, we collected and normalized data from 8 disease vocabularies and mapping sources to generate our datasets. Next, we built DisMaNET by integrating the generated datasets into a Neo4j graph database. Then we exploited the query mechanisms of Neo4j to cross-map disease terms of different vocabularies with a relevance score metric and contrasted the results with some state-of-the-art solutions. Finally, we made our system publicly available for its exploitation and evaluation both through a graphical user interface and REST APIs. Results DisMaNET contains almost half a million nodes and near nine hundred thousand edges, including hierarchical and mapping relationships. Its query capabilities enabled the detection of connections between disease vocabularies that are not present in major mapping sources such as UMLS and the Disease Ontology, even for rare diseases. Furthermore, DisMaNET was capable of obtaining more than 80% of the mappings with UMLS reported in MonDO and DisGeNET. Our tool was used successfully to complete the missing mappings in DISNET, a web-based system designed to extract knowledge from signs and symptoms retrieved from medical databases. Conclusions DisMaNET is a powerful, intuitive and publicly available system to cross-map terms from different disease vocabularies. Its completeness and the potential of network analysis make it a competitive alternative to existing mapping systems. Expansion with new sources, versioning and the improvement of the search and scoring algorithms are envisioned as future lines of work.

Funding Projects

Madrid Regional GovernmentIND2019/TIC-17159UnspecifiedUniversidad Politécnica de MadridPrograma de fomento de la investigación y la innovación (Doctorados Industriales)
Government of SpainRTI2018-094576-A-I00DISNETUnspecifiedCreation and analysis of disease networks for drug repurposing from heterogeneous data sources applied to rare diseases
Horizon 2020851255ARCTICAgencia Estatal Consejo Superior de Investigaciones CientíficasAir Transport as Information and Computation
Government of SpainMDM-2017-0711UnspecifiedUnspecifiedUnspecified

More information

Item ID: 67857
DC Identifier: https://oa.upm.es/67857/
OAI Identifier: oai:oa.upm.es:67857
DOI: 10.1016/j.cmpb.2021.106233
Official URL: https://doi.org/10.1016/j.cmpb.2021.106233
Deposited by: Memoria Investigacion
Deposited on: 22 Sep 2021 10:27
Last Modified: 30 Nov 2022 09:00
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