Search alternatives:
algorithm python » algorithm within (Expand Search), algorithms within (Expand Search)
python function » protein function (Expand Search)
algorithm gene » algorithm where (Expand Search), algorithm etc (Expand Search), algorithm pre (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
both function » body function (Expand Search), growth function (Expand Search), beach function (Expand Search)
Showing 41 - 60 results of 8,362 for search '(((( algorithm gene function ) OR ( algorithm python function ))) OR ( algorithm both function ))', query time: 0.39s Refine Results
  1. 41
    gmxapi usage examples.

    gmxapi usage examples. by M. Eric Irrgang (4487278)

    Published 2022
    Save to List
    Saved in:
  2. 42
    Image3_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.TIFF

    Image3_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.TIFF by Jian-Kun Song (11711756)

    Published 2022
    “…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …”
    Save to List
    Saved in:
  3. 43
    Image1_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.TIFF

    Image1_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.TIFF by Jian-Kun Song (11711756)

    Published 2022
    “…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …”
    Save to List
    Saved in:
  4. 44
    Image2_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.TIFF

    Image2_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.TIFF by Jian-Kun Song (11711756)

    Published 2022
    “…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …”
    Save to List
    Saved in:
  5. 45
    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm

    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm by José González-Gomariz (9610967)

    Published 2020
    “…This information is especially relevant for the researchers of the HPP who are interested in the generation and validation of new hypotheses about the functions of these proteins. Both the database and the web application are publicly available (https://github.com/ubioinformat/UPEfinder).…”
    Save to List
    Saved in:
  6. 46
    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm

    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm by José González-Gomariz (9610967)

    Published 2020
    “…This information is especially relevant for the researchers of the HPP who are interested in the generation and validation of new hypotheses about the functions of these proteins. Both the database and the web application are publicly available (https://github.com/ubioinformat/UPEfinder).…”
    Save to List
    Saved in:
  7. 47
    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm

    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm by José González-Gomariz (9610967)

    Published 2020
    “…This information is especially relevant for the researchers of the HPP who are interested in the generation and validation of new hypotheses about the functions of these proteins. Both the database and the web application are publicly available (https://github.com/ubioinformat/UPEfinder).…”
    Save to List
    Saved in:
  8. 48
    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm

    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm by José González-Gomariz (9610967)

    Published 2020
    “…This information is especially relevant for the researchers of the HPP who are interested in the generation and validation of new hypotheses about the functions of these proteins. Both the database and the web application are publicly available (https://github.com/ubioinformat/UPEfinder).…”
    Save to List
    Saved in:
  9. 49
    Python scripts used to model CPU errors by Poisson distribution density mass function and to draw graph of Poisson events (needs Matplot, SciPy, PysimpleGUI and NumPy)

    Python scripts used to model CPU errors by Poisson distribution density mass function and to draw graph of Poisson events (needs Matplot, SciPy, PysimpleGUI and NumPy) by Santhosh Kumar Rajamani (13023678)

    Published 2022
    Save to List
    Saved in:
  10. 50
    Algorithm framework.

    Algorithm framework. by Zongjin Li (38031)

    Published 2025
    Subjects:
    Save to List
    Saved in:
  11. 51
    Efficient algorithms to discover alterations with complementary functional association in cancer

    Efficient algorithms to discover alterations with complementary functional association in cancer by Rebecca Sarto Basso (6728921)

    Published 2019
    “…Among such patterns, <i>mutual exclusivity</i> has been employed by several recent methods that have shown its effectiveness in characterizing gene sets associated to cancer. Mutual exclusivity arises because of the complementarity, at the functional level, of alterations in genes which are part of a group (e.g., a <i>pathway</i>) performing a given function. …”
    Save to List
    Saved in:
  12. 52
    Linear relationship between ln(methadone concentration) and ln(methadone dose) by enantiomer and <i>CYP2B6</i> genotype function.

    Linear relationship between ln(methadone concentration) and ln(methadone dose) by enantiomer and <i>CYP2B6</i> genotype function. by Andrew H. Talal (8727396)

    Published 2020
    Save to List
    Saved in:
  13. 53
    Linear relationship between ln(methadone metabolism) and ln(methadone dose) by enantiomer and <i>CYP2B6</i> genotype function.

    Linear relationship between ln(methadone metabolism) and ln(methadone dose) by enantiomer and <i>CYP2B6</i> genotype function. by Andrew H. Talal (8727396)

    Published 2020
    Save to List
    Saved in:
  14. 54
    DataSheet2_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.CSV

    DataSheet2_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.CSV by Jian-Kun Song (11711756)

    Published 2022
    “…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …”
    Save to List
    Saved in:
  15. 55
    DataSheet3_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.CSV

    DataSheet3_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.CSV by Jian-Kun Song (11711756)

    Published 2022
    “…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …”
    Save to List
    Saved in:
  16. 56
    DataSheet1_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.pdf

    DataSheet1_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.pdf by Jian-Kun Song (11711756)

    Published 2022
    “…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …”
    Save to List
    Saved in:
  17. 57
    Verification of the in-line PS function.

    Verification of the in-line PS function. by Raul Castañeda (13932971)

    Published 2022
    Save to List
    Saved in:
  18. 58
    Available functions in the utility package.

    Available functions in the utility package. by Raul Castañeda (13932971)

    Published 2022
    Save to List
    Saved in:
  19. 59
    Table3_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX

    Table3_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX by Zhen Wang (72451)

    Published 2023
    “…Weighted gene coexpression network analysis (WGCNA) and two machine learning algorithms were employed to identify potential biomarkers for CRPC. …”
    Save to List
    Saved in:
  20. 60
    Table2_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX

    Table2_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX by Zhen Wang (72451)

    Published 2023
    “…Weighted gene coexpression network analysis (WGCNA) and two machine learning algorithms were employed to identify potential biomarkers for CRPC. …”
    Save to List
    Saved in:

Search Tools: