Enalos KNIME nodes

Blending cheminformatics, bioinformatics and nanoinformatics tools under KNIME

Categories:

NanoCommons

The H2020 Infrastructures project, NanoCommons, creates a community framework and infrastructure for reproducible science, and in particular for in silico workflows for nanomaterials safety assessment and beyond, by:

1. integration and federation of existing NMs characterisation and interaction mechanisms knowledge, protocols and data (beyond simple toxicity), along with quality assurance criteria and underpinning ontologies

2. compilation and development of a user-friendly interface for a suite of computational tools for mechanistic and statistical modelling, read-across, grouping, safe-by-design and life cycle assessment, and bench-marking of their predictive power; and

3. provision of (typically remote) access to its KnowledgeBase, modelling toolbox (predictive, grouping, risk assessment) and workflow optimisation, and the supporting expertise, to the broader user community.

This project has received funding from European Union Horizon 2020 Programme (H2020) via NanoCommons research infrastructure project under grant agreement nº 731032.

More information at: nanocommons.eu

One of the fruits of this project was the development of KNIME nodes for each model, tool and database, built within the project, to allow linkage into user-friendly and fully automated KNIME workflows that can be used for data management, processing and modelling purposes.

To acquire the NanoCommons nodes click here and select the "03-NanoCommons Nodes" option under the "Software title" menu.

Image analysis nodes

NanoXtract

Through this node, analysis of nanomaterials' Transmission Electron Microscopy (TEM) images can be performed through KNIME. The node gives access to the NanoXtract tool for the calculation of 18 image descriptors encoding geometrical characteristics of the depicted nanomaterials. More information about the analysis process and the calculated descriptors can be found in this publication.

NanoXtract 2

Model nodes

CNTSmiles

CNTSmiles is a fully validated predictive QNAR model correlating molecular descriptors of the decorating molecules of multi-walled carbon nanotubes and their toxicity, and biological activity (protein binding of carbonic anhydrase). A list of the binding molecules in SMILES format should be provided to execute this node. More information about the model can be found in the publication of Varsou et al., 2019.

CNTsdffile

CNTSmiles is a fully validated predictive QNAR model correlating molecular descriptors of the decorating molecules of multi-walled carbon nanotubes and their toxicity, and biological activity (protein binding of carbonic anhydrase). A file of the binding molecules in SDF format should be provided to execute this node. More information about the model can be found in the publication of Varsou et al., 2019.

Exposure

NanoCommons Exposure Node estimates the risk of triggering AOP 173 (Lung Fibrosis) in mice due to exposure to 20nm TiO2 engineered nanoparticles. This node is used in parallel with "ExposureScenario" and "ExposureRisk" nodes.

ExposureRisk

Risk assessment: Is performed by comparing the predicted distribution of TiO2 concentration in the lungs with Points of Departure (POD) that have been computed using a gene expression analysis workflow. The user can select the POD of interest among different pathways involved in AOP173 or the median value that defines the POD of the AOP and short term (1 day) or long term (28 days) effects. This node is used in parallel with "ExposureScenario" and "Exposure" nodes.

ExposureScenario

This node, gives access in four different exposure scenarios simulated using the GUIDENano tool. Depending on the selected scenario, the users can acquire the exposure dose profile of mice for 8 hours due to exposure to TiO2 nanoparticles. For each selected scenario information are provided within the node. This node is used in parallel with "ExposureRisk" and "Exposure" nodes.

ZetaPotential

Throught this node users, can employ a kNN/read-across model for the prediction of nanomaterials (NMs) zeta-potential based on the NM type of core, main elongation and medium's pH value. More information about the model can be found in the publication of Varsou et al., 2020.

Contact NovaMechanics Ltd

info[at]novamechanics[dot]com

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