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SimNetX: Interactive Support for Biomedical Data Analysis Using Patient Similarity Networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00098892%3A_____%2F25%3A10159371" target="_blank" >RIV/00098892:_____/25:10159371 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27240/25:10260260

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-031-82439-5_1" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-82439-5_1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-82439-5_1" target="_blank" >10.1007/978-3-031-82439-5_1</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    SimNetX: Interactive Support for Biomedical Data Analysis Using Patient Similarity Networks

  • Original language description

    Patient similarity networks (PSNs) are a widely used tool in biomedical data analysis. The most powerful feature of PSNs (and all networks in general) is the ability to visualize relatively complex data in a way that people can understand without expertise in statistics and machine learning. This aspect of data analysis is particularly important in biomedical data analysis, where data analysts, clinicians, and people from laboratories work in collaborative teams. However, working with PSNs requires steps that are usually solved in different systems or using programming libraries, e.g., in R or Python. This paper presents a tool whose design results from several years of experience with PSNs in biomedical data analysis. The tool focuses on the essential tasks of transforming vector data into PSNs and exploring them in detail, as well as on a high level of interactivity, e.g. allowing the formulation of preliminary hypotheses. We demonstrate the practical use of the tool on a well-known biological dataset.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Complex Networks &amp; Their Applications XIII

  • ISBN

    978-3-031-82438-8

  • ISSN

    1860-949X

  • e-ISSN

    1860-9503

  • Number of pages

    12

  • Pages from-to

    3-14

  • Publisher name

    Springer Cham

  • Place of publication

    Cham

  • Event location

    Istanbul

  • Event date

    Dec 10, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001489045000001