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knime workflow  (KNIME GmbH)

 
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    Structured Review

    KNIME GmbH knime workflow
    KNIME <t>workflow</t> for drug-likeness analysis (A) <t>and</t> <t>PMI</t> analysis (B). (C) Results of PMI analysis of natural compounds after drug-likeness selection. (D) Generation of the 3D pharmacophore hypothesis from the domain interface of NTD–CTD GSDMD
    Knime Workflow, supplied by KNIME GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/knime+workflows/knime+workflow/pmc12276684-119-21-21
    Average 90 stars, based on 1 article reviews
    knime workflow - by Bioz Stars, 2026-09
    90/100 stars

    Images

    1) Product Images from "Discovery of pyroptosis-inducing natural products in neuroblastomas: computational studies with experimental validation"

    Article Title: Discovery of pyroptosis-inducing natural products in neuroblastomas: computational studies with experimental validation

    Journal: BMC Complementary Medicine and Therapies

    doi: 10.1186/s12906-025-05004-8

    KNIME workflow for drug-likeness analysis (A) and PMI analysis (B). (C) Results of PMI analysis of natural compounds after drug-likeness selection. (D) Generation of the 3D pharmacophore hypothesis from the domain interface of NTD–CTD GSDMD
    Figure Legend Snippet: KNIME workflow for drug-likeness analysis (A) and PMI analysis (B). (C) Results of PMI analysis of natural compounds after drug-likeness selection. (D) Generation of the 3D pharmacophore hypothesis from the domain interface of NTD–CTD GSDMD

    Techniques Used: Selection

    Related Articles

    other:

    Article Title: Drug-induced cytotoxicity prediction in muscle cells, an application of the Cell Painting assay.
    Article Snippet: Code availability Jupyter Notebooks, Python scripts and KNIME workflows used in this study are accessible from the project GitHub repository at the following address: https://github.com/ romlambert/CytotoxPred Funding: This study is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 955830, “Future Toxicology: Better predicting Toxicant-induced cell fate.”.

    Article Title: High-content screening (HCS) workflows for FAIR image data management with OMERO.
    Article Snippet: All workflows and further instructions and conda environment setup to run the KNIME workflows are shared on the WorkflowHub (https://workflowhub.eu/projects/293).

    Article Title: Drug-induced cytotoxicity prediction in muscle cells, an application of the Cell Painting assay
    Article Snippet: Code availability Jupyter Notebooks, Python scripts and KNIME workflows used in this study are accessible from the project GitHub repository at the following address: https://github.com/romlambert/CytotoxPred


    Article Title: Refining Drug-Induced Cholestasis Prediction: An Explainable Consensus Model Integrating Chemical and Biological Fingerprints.
    Article Snippet: Separate KNIME workflows were established for the baseline model without target prediction and for each of the three cases including target prediction, to integrate unique predictions from all tools and consensus predictions shared by two or three tools.

    Article Title: High-content screening (HCS) workflows for FAIR image data management with OMERO
    Article Snippet: All workflows and further instructions and conda environment setup to run the KNIME workflows are shared on the WorkflowHub ( https://workflowhub.eu/projects/293 ).

    Biomarker Discovery:

    Article Title: Preliminary prediction of toxicologically relevant physicochemical properties of Novichoks: the first comparative in silico studies.
    Article Snippet: Advanced freely available and commercial in silico methods have been applied to predict the key physicochemical properties of Novichok agents, which are supertoxic organophosphorus compounds with limited experimental data due to their extreme toxicity and legal restrictions.. Toxicologically relevant physicochemical properties including boiling and melting points, vapour pressure, water solubility, partition coefficients (log P, log KOW, log KOA), Henry’s constants, and dissociation constants (pKa), were successfully predicted using appropriate in silico methods.. These properties are essential for estimating, based on computational models, the toxicological characteristics, potential environmental behavior, and bioaccumulation tendencies of these hazardous substances.

    Nuclear Magnetic Resonance:

    Article Title: Short Scalable Route to Bis-morpholine Spiroacetals and Oxazepane Analogues: Useful 3D-Scaffolds for Compound Library Assembly.
    Article Snippet: .. XXXX, XXX, XXX−XXX F characterization data, NMR data for all compounds, Xray crystallographic data for spiroacetals 7 and 23, library enumeration including KNIME workflows, and library analysis and selection of diversity subset for physical library synthesis (PDF) NMR spectra (PDF) .. XXXX, XXX, XXX−XXX F characterization data, NMR data for all compounds, Xray crystallographic data for spiroacetals 7 and 23, library enumeration including KNIME workflows, and library analysis and selection of diversity subset for physical library synthesis (PDF) NMR spectra (PDF)

    Selection:

    Article Title: Short Scalable Route to Bis-morpholine Spiroacetals and Oxazepane Analogues: Useful 3D-Scaffolds for Compound Library Assembly.
    Article Snippet: .. XXXX, XXX, XXX−XXX F characterization data, NMR data for all compounds, Xray crystallographic data for spiroacetals 7 and 23, library enumeration including KNIME workflows, and library analysis and selection of diversity subset for physical library synthesis (PDF) NMR spectra (PDF) .. XXXX, XXX, XXX−XXX F characterization data, NMR data for all compounds, Xray crystallographic data for spiroacetals 7 and 23, library enumeration including KNIME workflows, and library analysis and selection of diversity subset for physical library synthesis (PDF) NMR spectra (PDF)



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    Image Search Results


    KNIME workflow for drug-likeness analysis (A) and PMI analysis (B). (C) Results of PMI analysis of natural compounds after drug-likeness selection. (D) Generation of the 3D pharmacophore hypothesis from the domain interface of NTD–CTD GSDMD

    Journal: BMC Complementary Medicine and Therapies

    Article Title: Discovery of pyroptosis-inducing natural products in neuroblastomas: computational studies with experimental validation

    doi: 10.1186/s12906-025-05004-8

    Figure Lengend Snippet: KNIME workflow for drug-likeness analysis (A) and PMI analysis (B). (C) Results of PMI analysis of natural compounds after drug-likeness selection. (D) Generation of the 3D pharmacophore hypothesis from the domain interface of NTD–CTD GSDMD

    Article Snippet: Subsequent analysis focused on the molecular shape of the filtered compounds, employing the normalized principal moment of inertia (PMI) in a KNIME workflow (Fig. B, C).

    Techniques: Selection