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neural network tool  (MathWorks Inc)


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    Structured Review

    MathWorks Inc neural network tool
    Neural Network Tool, supplied by MathWorks Inc, 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/network+tool/us12368288-82-5-5
    Average 90 stars, based on 1 article reviews
    neural network tool - by Bioz Stars, 2026-11
    90/100 stars

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    Related Articles

    other:

    Article Title: A hybrid optimization approach for intelligent manufacturing in plastic injection molding by using artificial neural network and genetic algorithm
    Article Snippet: Therefore, the developed multilayer Neural Network is (7-13-4) as shown in Fig. on representation graph (Fig. a) and in Matlab neural network tool (Fig. b).

    Article Title: Noise Estimation and Type Identification in Natural Scene and Medical Images using Deep Learning Approaches
    Article Snippet: The neural tool MATLAB is employed to design the neural fit model.

    Article Title: Method of predicting central fishing ground of flying squid family ommastrephidae
    Article Snippet: Using Matlab neural network tool, the central fishing ground models of Humboldt squid (Dosidicus gigas) in the southeast Pacific Ocean, in different spatial and temporal dimensions and environmental factors, are established according to the BP neural network modeling method; and the accuracies of the models and the ARV values of the entire samples are calculated.

    Article Title: Method of predicting central fishing ground of flying squid family ommastrephidae
    Article Snippet: Using Matlab neural network tool, the central fishing ground prediction models of flying squid (Ommasrephidae) in the northwest Pacific Ocean, in different spatial and temporal dimensions and environmental factors, are established according to the modeling method; and the accuracies of the models and the ARV values of the entire samples from 2003 to 2011 are calculated (as shown in FIGS. 8-11).

    Article Title: Clustering approach with self-organizing maps for unmanned aerial vehicle response to post-earthquake fires: An application for Istanbul
    Article Snippet: In the next section, the application has been conducted using a code written with the help of MATLAB Neural Network Tool is presented.

    Construct:

    Article Title: GIS mechanical fault diagnosis method and device
    Article Snippet: .. In a specific embodiment, the MATLAB neural network tool is used to construct a single hidden layer BP neural network, with 8 neurons in the input layer and 3 neurons in the output layer. ..

    Software:

    Article Title: Optimization of Millet Malting Parameters Using Artificial Neural Network and Response Surface Methodology
    Article Snippet: .. To determine the optimal neural network, the neural network tool in MATLAB (R 2013a) software was used. ..

    Viscosity:

    Article Title: Closing Thoughts on the Proposition of Improving Drift Velocity Closure Relationship for Multiphase Flow Models
    Article Snippet: .. Statistical analyses of the pipe and fluid parameters Pipe orientation Range of values Pipe ID (m) Liquid density Kg/m3 Liquid viscosity cP Surface tension N/m Froude number Horizontal Min 2.20E-02 8.60E+02 1.00E+00 1.51E-02 1.49E-02 Max 1.52E-01 9.98E+02 1.14E+03 7.20E-02 5.05E-01 Average 7.03E-02 9.02E+02 2.73E+02 3.42E-02 3.24E-01 Vertical Min 4.00E-03 7.87E+02 5.44E-01 2.02E-02 5.90E-05 Max 1.52E-01 1.51E+03 3.33E+04 8.70E-02 3.88E-01 Average 4.15E-02 1.04E+03 1.19E+03 4.57E-02 2.31E-01 Inclined Min 4.00E-03 7.87E+02 5.44E-01 2.02E-02 5.90E-05 Max 1.52E-01 1.51E+03 3.33E+04 8.70E-02 3.88E-01 Average 4.15E-02 1.04E+03 1.19E+03 4.57E-02 2.31E-01 The MATLAB® Neural Network tool was used for the development of the drift velocity neural network models. ..



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    Qiagen ingenuity pathway analysis network pathway tool
    <t>Coronavirus</t> pathogenesis pathway overlaid with gene expression data of iPSCs. The coronavirus pathogenesis pathway was overlaid with iPSCs infected with SARS-CoV-2. The expression log ratio of iPSCs infected with SARS-CoV-2 (0.006 MOI) to mock infection was colored in red (upregulated) or green (downregulated) (as of April 2024). Gene expression data ( GSE156754 ) of iPSCs with mock infection and iPSCs infected with SARS-CoV-2 were compared in the <t>IPA</t> database. Red or green coloring indicates upregulated or downregulated gene expression, respectively. Orange or blue coloring indicates predicted activation or inhibition, respectively. The intensity of the colors indicates the degree of up- or downregulation. An orange or blue line indicates activation or inhibition, respectively.
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    Image Search Results


    Coronavirus pathogenesis pathway overlaid with gene expression data of iPSCs. The coronavirus pathogenesis pathway was overlaid with iPSCs infected with SARS-CoV-2. The expression log ratio of iPSCs infected with SARS-CoV-2 (0.006 MOI) to mock infection was colored in red (upregulated) or green (downregulated) (as of April 2024). Gene expression data ( GSE156754 ) of iPSCs with mock infection and iPSCs infected with SARS-CoV-2 were compared in the IPA database. Red or green coloring indicates upregulated or downregulated gene expression, respectively. Orange or blue coloring indicates predicted activation or inhibition, respectively. The intensity of the colors indicates the degree of up- or downregulation. An orange or blue line indicates activation or inhibition, respectively.

    Journal: Current Issues in Molecular Biology

    Article Title: Artificial Intelligence Approach in Machine Learning-Based Modeling and Networking of the Coronavirus Pathogenesis Pathway †

    doi: 10.3390/cimb47060466

    Figure Lengend Snippet: Coronavirus pathogenesis pathway overlaid with gene expression data of iPSCs. The coronavirus pathogenesis pathway was overlaid with iPSCs infected with SARS-CoV-2. The expression log ratio of iPSCs infected with SARS-CoV-2 (0.006 MOI) to mock infection was colored in red (upregulated) or green (downregulated) (as of April 2024). Gene expression data ( GSE156754 ) of iPSCs with mock infection and iPSCs infected with SARS-CoV-2 were compared in the IPA database. Red or green coloring indicates upregulated or downregulated gene expression, respectively. Orange or blue coloring indicates predicted activation or inhibition, respectively. The intensity of the colors indicates the degree of up- or downregulation. An orange or blue line indicates activation or inhibition, respectively.

    Article Snippet: The coronavirus pathogenesis pathway was analyzed using the Ingenuity Pathway Analysis (IPA) network pathway tool [ , ] ( https://digitalinsights.qiagen.com/products-overview/discovery-insights-portfolio/analysis-and-visualization/qiagen-ipa/ ) (accessed on 16 May 2025).

    Techniques: Gene Expression, Infection, Expressing, Activation Assay, Inhibition