Robust Connectivity Scores for Gene Co-Expression Network Analysis

Alin A., Ölmez A.

2021 Virtual International Workshop ​of G.S.I., Samos, Greece, 24 - 26 September 2021, pp.17-25, (Summary Text)

  • Publication Type: Conference Paper / Summary Text
  • City: Samos
  • Country: Greece
  • Page Numbers: pp.17-25
  • Dokuz Eylül University Affiliated: Yes

Abstract

With the advantage of high throughput technologies, gene network analysis became a crucial tool in bioinformatics. Large-scale microarray expression gene network studies explore the identification, functions and relations of individual genes or their products across biological conditions. One of the network-based methods is gene coexpression networks, which are used for describing associations between high-throughput expression patterns of genes. Connectivity scores, calculated using model-based approaches, can be used to build edges in networks. Herein, we introduce new model-based scores that are robust to noise and non-normality in the data.