ECMarker: Interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages

Authors

Ting Jin

Published

June 12, 2020

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DOI

10.1101/825414

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ECMarker: Interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages

Authors

Ting Jin

Published

June 12, 2020

Add a comment...

Supporters

Support the authors with ResearchCoin

Preprint Server

Topics

DOI

10.1101/825414

License

cc-no

Supporters

Support the authors with ResearchCoin

Preprint Server

Topics

DOI

10.1101/825414

License

cc-no

Paper

Paper

Paper

Paper

ECMarker: Interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages

Supporters

Preprint Server

Topics

DOI

License

ECMarker: Interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages

Supporters

Preprint Server

Topics

DOI

License

Supporters

Preprint Server

Topics

DOI

License