title: Gene regulatory network inference using PLS-based methods.
abstract: BACKGROUND
  Inferring the topology of gene regulatory networks (GRNs) from microarray gene expression data has many potential applications, such as identifying candidate drug targets and providing valuable insights into the biological processes. It remains a challenge due to the fact that the data is noisy and high dimensional, and there exists a large number of potential interactions.
  
  
  RESULTS
  We introduce an ensemble gene regulatory network inference method PLSNET, which decomposes the GRN inference problem with p genes into p subproblems and solves each of the subproblems by using Partial least squares (PLS) based feature selection algorithm. Then, a statistical technique is used to refine the predictions in our method. The proposed method was evaluated on the DREAM4 and DREAM5 benchmark datasets and achieved higher accuracy than the winners of those competitions and other state-of-the-art GRN inference methods.
  
  
  CONCLUSIONS
  Superior accuracy achieved on different benchmark datasets, including both in silico and in vivo networks, shows that PLSNET reaches state-of-the-art performance.
authors.affiliation: Department of Electronic Engineering, Xiamen University, Fujian, 361005, China.|Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518000, China.
authors.forename: Shun
authors.initials: S
authors.lastname: Guo
authors.affiliation: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518000, China.
authors.forename: Qingshan
authors.initials: Q
authors.lastname: Jiang
authors.affiliation: School of Mathematics and Computer Science, Fujian Normal University, Fujian, 350117, China.
authors.forename: Lifei
authors.initials: L
authors.lastname: Chen
authors.affiliation: Department of Electronic Engineering, Xiamen University, Fujian, 361005, China. dhguo@xmu.edu.cn.
authors.forename: Donghui
authors.initials: D
authors.lastname: Guo
mesh_terms: D015870:Gene Expression; D053263:Gene Regulatory Networks; D016018:Least-Squares Analysis; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*
keywords: Ensemble; Gene Regulatory Network inference; Gene expression data; Partial least squares (PLS)