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Identification of disease genes and assessment of eye-related diseases caused by disease genes using JMFC and GDLNN

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  • Samar Jyoti Saikia
  • S. R. Nirmala

Abstract

Early detection of disease genes helps humans to recover from certain gene-related diseases, like genetic eye diseases. This work identifies the possibility of eye diseasesfor the disease genes utilizing a Gaussian-activation function (G)-centric deeplearning neural network (GDLNN) model. In this work, human genes are selected by computing structural similarity and genes are clustered as disease genesand normal genes by using the JMFC clustering algorithm. Levy flight and Crossover and Mutation (LCM) centric Chicken Swarm Optimization (LCM-CSO) is employed for feature selection and GDLNN classifies the eye-related diseases for the input genes using the selected features.

Suggested Citation

  • Samar Jyoti Saikia & S. R. Nirmala, 2022. "Identification of disease genes and assessment of eye-related diseases caused by disease genes using JMFC and GDLNN," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 25(4), pages 359-370, March.
    • Handle: RePEc:taf:gcmbxx:v:25:y:2022:i:4:p:359-370
    DOI: 10.1080/10255842.2021.1955358
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