Gene prediction of aging-related diseases based on DNN and Mashup.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: At present, the bioinformatics research on the relationship between aging-related diseases and genes is mainly through the establishment of a machine learning multi-label model to classify each gene. Most of the existing methods for predicting pathogenic genes mainly rely on specific types of gene features, or directly encode multiple features with different dimensions, use the same encoder to concatenate and predict the final results, which will be subject to many limitations in the applicability of the algorithm. Possible shortcomings of the above include: incomplete coverage of gene features by a single type of biomics data, overfitting of small dimensional datasets by a single encoder, or underfitting of larger dimensional datasets.

Authors

  • Junhua Ye
    College of Geology Engineering and Geomantic, Chang'an University, 710054 Xi'an , Shanxi, China.
  • Shunfang Wang
  • Xin Yang
    Department of Oral Maxillofacial-Head Neck Oncology, Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, China.
  • Xianjun Tang
    School of Information Science and Engineering, Yunnan University, KunMing, 650000, China.