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Showing 161 - 180 results of 6,835 for search '(((( algorithm gene function ) OR ( algorithm gpcr function ))) OR ( algorithm python function ))', query time: 0.45s Refine Results
  1. 161
    Antibody challenge outcomes.

    Antibody challenge outcomes. by Andrea Blasco (7439102)

    Published 2019
    “…Also shown is the benchmark algorithm implemented in Python (A1) and C++ (A2); note that benchmark algorithms A1 and A2 have perfect accuracy (<i>ACC</i> equal to unity). …”
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  2. 162
    Functions of genes, detected simultaneously in 3 "diseased" blocks («Prostate Disease», «PCa», «Not PCa») and missing in the "Healthy" block and one gene (HRAS), found only in the block "Healthy" (STRING data).

    Functions of genes, detected simultaneously in 3 "diseased" blocks («Prostate Disease», «PCa», «Not PCa») and missing in the "Healthy" block and one gene (HRAS), found only in the... by O. E. Bryzgunova (6577043)

    Published 2019
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  3. 163
    Functional SNP region.

    Functional SNP region. by Mahmudul Hasan Rifat (12884620)

    Published 2022
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  4. 164
    An example of the algorithm of the ORFanID engine is explained in a UML flow chart diagram.

    An example of the algorithm of the ORFanID engine is explained in a UML flow chart diagram. by Richard S. Gunasekera (6752072)

    Published 2023
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  5. 165
    Data_Sheet_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.PDF

    Data_Sheet_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.PDF by Hong Gu (68558)

    Published 2020
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  6. 166
    Data_Sheet_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.PDF

    Data_Sheet_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.PDF by Hong Gu (68558)

    Published 2021
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  7. 167
    Functional enrichment analysis of hub genes.

    Functional enrichment analysis of hub genes. by Tingting Liu (267387)

    Published 2025
    “…<p>(A) Hub genes were selected using the MCC algorithm. (B) Enrichment analysis of biological processes (BP) hub genes. …”
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  8. 168
    Functional impact of non-preserved modules-based gene ontology (biological processes category).

    Functional impact of non-preserved modules-based gene ontology (biological processes category). by Bahman Panahi (7323578)

    Published 2024
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  9. 169
    Classification thresholds and prediction algorithms for novel PGx variants.

    Classification thresholds and prediction algorithms for novel PGx variants. by Ewa Goljan (3463487)

    Published 2022
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  10. 170
    Penalty functions used in different methods.

    Penalty functions used in different methods. by Souvik Seal (12437166)

    Published 2023
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  11. 171
    Distributions of model parameters mirror differentially expressed ion channel genes.

    Distributions of model parameters mirror differentially expressed ion channel genes. by Daniele Linaro (227790)

    Published 2022
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  12. 172
    Empirical cumulative distribution functions for DMCs.

    Empirical cumulative distribution functions for DMCs. by Koyel Majumdar (20416871)

    Published 2024
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  13. 173
    Tumor suppressor genes with a frameshift mutation at frequency of 5% or higher.

    Tumor suppressor genes with a frameshift mutation at frequency of 5% or higher. by Alexis M. Thornton (11068403)

    Published 2021
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  14. 174
    Tumor suppressor genes with two frameshift mutations with frequency of 1% or higher.

    Tumor suppressor genes with two frameshift mutations with frequency of 1% or higher. by Alexis M. Thornton (11068403)

    Published 2021
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  15. 175
    Our algorithms process large data sets within a minute.

    Our algorithms process large data sets within a minute. by Manu Aggarwal (15990691)

    Published 2023
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  16. 176
    Genes that contribute to PCA and GO terms of enriched and differentially expressed genes. GO, gene ontology; PCA, principal component analysis.

    Genes that contribute to PCA and GO terms of enriched and differentially expressed genes. GO, gene ontology; PCA, principal component analysis. by Tomokatsu Udagawa (11675636)

    Published 2021
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  17. 177
    Functional enrichment analysis of DEGs.

    Functional enrichment analysis of DEGs. by Huiling Deng (4427161)

    Published 2022
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  18. 178
    Test functions.

    Test functions. by Kejia Liu (5699651)

    Published 2025
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  19. 179
    eVIP identifies functional differences between two RNF43 frameshift mutations.

    eVIP identifies functional differences between two RNF43 frameshift mutations. by Alexis M. Thornton (11068403)

    Published 2021
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  20. 180
    KEGG analysis bubble plot for other four module.

    KEGG analysis bubble plot for other four module. by Zongjin Li (38031)

    Published 2025
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