WERFE: A Gene Selection Algorithm Based on Recursive Feature Elimination and Ensemble Strategy.
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ABSTRACT:
SUBMITTER: Chen Q
PROVIDER: S-EPMC7270206 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
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Project description:AIM:Pancreatic cancer is one of the worst malignant tumors in prognosis. Therefore, to reduce the mortality rate of pancreatic cancer, early diagnosis and prompt treatment are particularly important. RESULTS:We put forward a new feature-selection method that was used to find clinical markers for pancreatic cancer by combination of Support Vector Machine Recursive Feature Elimination (SVM-RFE) and Large Margin Distribution Machine Recursive Feature Elimination (LDM-RFE) algorithms. As a result, seven differentially expressed genes were predicted as specific biomarkers for pancreatic cancer because of their highest accuracy of classification on cancer and normal samples. CONCLUSION:Three (MMP7, FOS and A2M) out of the seven predicted gene markers were found to encode proteins secreted into urine, providing potential diagnostic evidences for pancreatic cancer.
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