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implementations of genie3  (MathWorks Inc)


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    MathWorks Inc implementations of genie3
    Implementations Of Genie3, 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/implementations+of+genie3/pm34673384-175-5-2
    Average 90 stars, based on 1 article reviews
    implementations of genie3 - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    Comparison:

    Article Title: Enhancing gene regulatory networks inference through hub-based data integration.
    Article Snippet: One of the main research topics in computational biology is Gene Regulatory Network (GRN) reconstruction that refers to inferring the relationships between genes involved in regulating cell conditions in response to internal or external stimuli.. To this end, most computational methods use only transcriptional gene expression data to reconstruct gene regulatory networks, but recent studies suggest that gene expression data must be integrated with other types of data to obtain more accurate models predicting real relationships between genes.. In this study, a diffusion-based method is enhanced to integrate biological data of network types besides structural prior knowledge.

    Article Title: Gene regulatory network inference using PLS-based methods
    Article Snippet: We use the Matlab implementations of GENIE3 and TIGRESS, while ARACNE and CLR are run in the minet R package [ ].

    Article Title: TIGRESS: Trustful Inference of Gene REgulation using Stability Selection
    Article Snippet: We use the MATLAB implementations of CLR [ ] and GENIE3 [ ].



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    implementations of genie3  (MathWorks Inc)
    90
    MathWorks Inc implementations of genie3
    Implementations Of Genie3, 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/implementations+of+genie3/pm34673384-175-5-2
    Average 90 stars, based on 1 article reviews
    implementations of genie3 - by Bioz Stars, 2026-09
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    implementation of genie3  (MathWorks Inc)
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    AUPR and AUROC scores for DREAM4 Multifactorial challenge.
    Implementation Of Genie3, 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/implementations+of+genie3/pmc02946910-126-8-5
    Average 90 stars, based on 1 article reviews
    implementation of genie3 - by Bioz Stars, 2026-09
    90/100 stars
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    AUPR and AUROC scores for DREAM4 Multifactorial challenge.

    Journal: PLoS ONE

    Article Title: Inferring Regulatory Networks from Expression Data Using Tree-Based Methods

    doi: 10.1371/journal.pone.0012776

    Figure Lengend Snippet: AUPR and AUROC scores for DREAM4 Multifactorial challenge.

    Article Snippet: To fix ideas, with our MatLab implementation of GENIE3, it takes 6.5 minutes to infer the five networks of the DREAM4 challenge and 7 hours to infer the E. coli network (with known transcription factors), in both cases with Random Forests and , where is the number of potential regulators (see later for the details of these experiments).

    Techniques:

    AUPR and AUROC p-values for DREAM4 Multifactorial challenge.

    Journal: PLoS ONE

    Article Title: Inferring Regulatory Networks from Expression Data Using Tree-Based Methods

    doi: 10.1371/journal.pone.0012776

    Figure Lengend Snippet: AUPR and AUROC p-values for DREAM4 Multifactorial challenge.

    Article Snippet: To fix ideas, with our MatLab implementation of GENIE3, it takes 6.5 minutes to infer the five networks of the DREAM4 challenge and 7 hours to infer the E. coli network (with known transcription factors), in both cases with Random Forests and , where is the number of potential regulators (see later for the details of these experiments).

    Techniques:

    Overall scores of GENIE3 for DREAM4 networks.

    Journal: PLoS ONE

    Article Title: Inferring Regulatory Networks from Expression Data Using Tree-Based Methods

    doi: 10.1371/journal.pone.0012776

    Figure Lengend Snippet: Overall scores of GENIE3 for DREAM4 networks.

    Article Snippet: To fix ideas, with our MatLab implementation of GENIE3, it takes 6.5 minutes to infer the five networks of the DREAM4 challenge and 7 hours to infer the E. coli network (with known transcription factors), in both cases with Random Forests and , where is the number of potential regulators (see later for the details of these experiments).

    Techniques:

    Asymmetry of predicted and gold standard networks.

    Journal: PLoS ONE

    Article Title: Inferring Regulatory Networks from Expression Data Using Tree-Based Methods

    doi: 10.1371/journal.pone.0012776

    Figure Lengend Snippet: Asymmetry of predicted and gold standard networks.

    Article Snippet: To fix ideas, with our MatLab implementation of GENIE3, it takes 6.5 minutes to infer the five networks of the DREAM4 challenge and 7 hours to infer the E. coli network (with known transcription factors), in both cases with Random Forests and , where is the number of potential regulators (see later for the details of these experiments).

    Techniques: