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Showing 241 - 260 results of 956 for search '(( algorithm fibrin function ) OR ((( algorithm python function ) OR ( algorithm both function ))))', query time: 0.25s Refine Results
  1. 241
    Table 2_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx

    Table 2_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
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  2. 242
    Table 1_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx

    Table 1_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
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  3. 243
    Table 4_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx

    Table 4_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
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  4. 244
    Table 5_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx

    Table 5_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

    Published 2025
    “…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”
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  5. 245
    Calculation FFR, IMR and CFR.

    Calculation FFR, IMR and CFR. by Ainhoa Pérez-Guerrero (21377457)

    Published 2025
    “…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …”
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  6. 246
    Definition of events.

    Definition of events. by Ainhoa Pérez-Guerrero (21377457)

    Published 2025
    “…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …”
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  7. 247
    Eligibility criteria.

    Eligibility criteria. by Ainhoa Pérez-Guerrero (21377457)

    Published 2025
    “…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …”
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  8. 248
    Secondary endpoints.

    Secondary endpoints. by Ainhoa Pérez-Guerrero (21377457)

    Published 2025
    “…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …”
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  9. 249
    Flowchart of BWEMFO.

    Flowchart of BWEMFO. by Jingjing Ma (419752)

    Published 2025
    “…The scalability of the algorithm is confirmed through benchmark functions. …”
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  10. 250
    Various MFOs from three mechanisms.

    Various MFOs from three mechanisms. by Jingjing Ma (419752)

    Published 2025
    “…The scalability of the algorithm is confirmed through benchmark functions. …”
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  11. 251
    The flowchart of MFO.

    The flowchart of MFO. by Jingjing Ma (419752)

    Published 2025
    “…The scalability of the algorithm is confirmed through benchmark functions. …”
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  12. 252
    Parameters.

    Parameters. by Jingjing Ma (419752)

    Published 2025
    “…The scalability of the algorithm is confirmed through benchmark functions. …”
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  13. 253
    Riemann Hypothesis Solution: A Structured Hilbert-Polya Operator Realization via Entropy Geometry

    Riemann Hypothesis Solution: A Structured Hilbert-Polya Operator Realization via Entropy Geometry by Jennifer Bulyaki (22283308)

    Published 2025
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  14. 254
    Video 5_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4

    Video 5_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)

    Published 2025
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  15. 255
    Video 8_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4

    Video 8_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)

    Published 2025
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  16. 256
    Video 6_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4

    Video 6_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)

    Published 2025
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  17. 257
    Video 1_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4

    Video 1_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)

    Published 2025
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  18. 258
    Supplementary file 1_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.docx

    Supplementary file 1_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.docx by Hannah James (6551678)

    Published 2025
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  19. 259
    Video 9_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4

    Video 9_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)

    Published 2025
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  20. 260
    Video 3_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4

    Video 3_Biologically informed algorithms for modeling cattle response to auditory cues and driving simulations in virtual fencing systems.mp4 by Hannah James (6551678)

    Published 2025
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