A deep learning approach for orphan gene identification in moso bamboo (Phyllostachys edulis) based on the CNN + Transformer model.

Journal: BMC bioinformatics
Published Date: May 5, 2022

Abstract

BACKGROUND: Orphan gene play an important role in the environmental stresses of many species and their identification is a critical step to understand biological functions. Moso bamboo has high ecological, economic and cultural value. Studies have shown that the growth of moso bamboo is influenced by various stresses. Several traditional methods are time-consuming and inefficient. Hence, the development of efficient and high-accuracy computational methods for predicting orphan genes is of great significance.

Authors

  • Xiaodan Zhang
    Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment, Anhui Agriculture University, Hefei, 230001, China.
  • Jinxiang Xuan
    Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment, Anhui Agriculture University, Hefei, 230001, China.
  • Chensong Yao
    Graduate School, Anhui Agricultural University, Hefei, 230036, China.
  • Qijuan Gao
    Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment, Anhui Agriculture University, Hefei, 230001, China.
  • Lianglong Wang
    Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment, Anhui Agriculture University, Hefei, 230001, China.
  • Xiu Jin
    Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment, Anhui Agriculture University, Hefei, 230001, China. jinxiu123@ahau.edu.cn.
  • Shaowen Li
    Anhui Province Key Laboratory of Smart Agricultural Technology and Equipment, Anhui Agriculture University, Hefei, 230001, China. liahau@163.com.

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