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Modelling of Nanomaterials Toxicity by the Means of Relational Machine Learning

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378041%3A_____%2F17%3A00490568" target="_blank" >RIV/68378041:_____/17:00490568 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Modelling of Nanomaterials Toxicity by the Means of Relational Machine Learning

  • Original language description

    The main goal of this chapter was to introduce a novel paradigm for nano-QSAR to a broader scientific community. The proposal stems from relational machine learning and addresses the heterogenity of current nanotoxicity-related data. We commence with the discussion of safer-by-design principle in nanotoxicity predictive modeling and summarize the main shortcomings of the current modeling techniques. Then, we introduce a small, yet well-defined nanotoxicity modelling task that will serve as a case-study. The respective data set contains relevant enumerated descriptors as well as the toxicity targets. Then, we define the problem in terms of relational probabilistic modelling.

  • Czech name

  • Czech description

Classification

  • Type

    C - Chapter in a specialist book

  • CEP classification

  • OECD FORD branch

    10602 - Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology

Result continuities

  • Project

    <a href="/en/project/LO1508" target="_blank" >LO1508: Genomics and proteomics in the study of mechanisms of biological effects of produced nanoparticles</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Book/collection name

    Nanomaterials in Biomedical research

  • ISBN

    978-80-906655-5-2

  • Number of pages of the result

    5

  • Pages from-to

    4-8

  • Number of pages of the book

    140

  • Publisher name

    Proxima Tisk, s.r.o.

  • Place of publication

    Praha 3

  • UT code for WoS chapter