Construction of Transcriptional Regulatory Network of Alzheimer’s Disease Based on PANDA Algorithm

Jieyuan Ding, Wei Kong, Xiaoyang Mou, Shuaiqun Wang

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The focus of modern biomedical research concentrates on molecular level regulatory mechanisms and how the normal and abnormal phenotypes of tissue functional are affected by regulatory mechanisms. Most of the research on regulatory mechanism starts from the reconstruction of gene regulation network. At present, a large number of reconstruction methods construct the network using a single data set. These methods of inferring and predicting the relationship between the target gene and the transcription factor (TF) can be used to identify individual interactions between genes, while there is not much research on the interaction of many functional-related genes. In this paper, an integrated approach based on multi-data fusion is used to reconstruct the network on Alzheimer’s disease (AD) which is the most common form of dementia. It not only considers the interaction between many functional-related genes and the TFs that have important implications for regulatory mechanisms, but also detects new genes associated with specific gene function expression. Protein interaction data, motif data and gene expression data of AD were integrated to gain insight into the underlying biological processes of AD. This method takes into account the TF on the target gene regulation, at the same time also considers co-expression mechanism of the TF and co-regulatory mechanism of the target gene. Eventually, not only a number of genes such as E2F4 and ATF1 related to the pathogenesis of AD have been identified, but also several significant biological processes, such as immunoregulation and neurogenesis, have been found to be associated with AD.

Original languageEnglish (US)
Pages (from-to)226-236
Number of pages11
JournalInterdisciplinary Sciences: Computational Life Sciences
Volume11
Issue number2
DOIs
StatePublished - Jun 1 2019

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science Applications
  • Health Informatics

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