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Showing 1 - 20 results of 65 for search 'multiple sources interactions algorithm', query time: 0.28s Refine Results
  1. 1
    Attack and defense behaviors with the sensory–motor algorithm between multiple predators and prey.

    Attack and defense behaviors with the sensory–motor algorithm between multiple predators and prey. by Hiroyuki Ichijo (13891153)

    Published 2025
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  2. 2
    Algorithm parameter settings employed in the experiments on simulated data.

    Algorithm parameter settings employed in the experiments on simulated data. by Liyan Sun (760586)

    Published 2024
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  3. 3
    The gene network of the epistatic interactions detected for Bipolar Disorder.

    The gene network of the epistatic interactions detected for Bipolar Disorder. by Liyan Sun (760586)

    Published 2024
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  4. 4
    The SNP network of the epistatic interactions detected for Bipolar Disorder.

    The SNP network of the epistatic interactions detected for Bipolar Disorder. by Liyan Sun (760586)

    Published 2024
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  5. 5
    Estimated marginal means of stress source.

    Estimated marginal means of stress source. by Benjamin A. Hives (5592104)

    Published 2025
    “…Random forest analyses found that, after accounting for variance from other factors and considering complex interactions, life satisfaction (relative importance = 1.00), negative social interactions (0.99), primary stress source (0.85), and age (0.77) were the most important correlates of psychological stress. …”
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  6. 6
    Genes of the epistastic interactions detected on the seven GWAS data using Epi-SSA.

    Genes of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

    Published 2024
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  7. 7
    Epistatic interactions found by Epi-SSA (n = 600 maxG = 800000).

    Epistatic interactions found by Epi-SSA (n = 600 maxG = 800000). by Liyan Sun (760586)

    Published 2024
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  8. 8
    Gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA.

    Gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

    Published 2024
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  9. 9
    Part of genes of the epistastic interactions detected on the seven GWAS data using Epi-SSA.

    Part of genes of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

    Published 2024
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  10. 10
    Part of epistatic interactions found by Epi-SSA (n = 600 maxG = 800000).

    Part of epistatic interactions found by Epi-SSA (n = 600 maxG = 800000). by Liyan Sun (760586)

    Published 2024
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  11. 11
    Part of gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA.

    Part of gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

    Published 2024
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  12. 12
    Machine Learning Modeling for ABC Transporter Efflux and Inhibition: Data Curation, Model Development, and New Compound Interaction Predictions

    Machine Learning Modeling for ABC Transporter Efflux and Inhibition: Data Curation, Model Development, and New Compound Interaction Predictions by Nada J. Daood (18626266)

    Published 2025
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  13. 13
    Statistical comparisons of the proportion of recapitulated genes for three substance use disorders.

    Statistical comparisons of the proportion of recapitulated genes for three substance use disorders. by Everest U. Castaneda (21553580)

    Published 2025
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  14. 14
    Scheme for building heterogeneous graphs and subsequent RWR.

    Scheme for building heterogeneous graphs and subsequent RWR. by Everest U. Castaneda (21553580)

    Published 2025
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  15. 15
    Execution time comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset.

    Execution time comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset. by Liyan Sun (760586)

    Published 2024
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  16. 16
    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DNME 1000 dataset.

    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DNME 1000 dataset. by Liyan Sun (760586)

    Published 2024
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  17. 17
    Power comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset.

    Power comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset. by Liyan Sun (760586)

    Published 2024
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  18. 18
    Execution time comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 100 dataset.

    Execution time comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 100 dataset. by Liyan Sun (760586)

    Published 2024
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  19. 19
    The brief description on the WTCCC dataset.

    The brief description on the WTCCC dataset. by Liyan Sun (760586)

    Published 2024
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  20. 20
    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset.

    F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset. by Liyan Sun (760586)

    Published 2024
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