title: Gene Networks in Plant Biology: Approaches in Reconstruction and Analysis.
abstract: Even though vast amounts of genome-wide gene expression data have become available in plants, it remains a challenge to effectively mine this information for the discovery of genes and gene networks, for instance those that control agronomically important traits. These networks reflect potential interactions among genes and, therefore, can lead to a systematic understanding of the molecular mechanisms underlying targeted biological processes. We discuss methods to analyze gene networks using gene expression data, specifically focusing on four common statistical approaches used to reconstruct networks: correlation, feature selection in supervised learning, probabilistic graphical model, and meta-prediction. In addition, we discuss the effective use of these methods for acquiring an in-depth understanding of biological systems in plants.
authors.affiliation: Center for Applied Genetic Technologies, University of Georgia, 111 Riverbend Road, Athens, GA 30602; Institute of Plant Breeding, Genetics and Genomics, University of Georgia, 111 Riverbend Road, Athens, GA 30602; Department of Statistics, University of Georgia, 101 Cedar Street, Athens, GA 30602.
authors.forename: Yupeng
authors.initials: Y
authors.lastname: Li
authors.affiliation: Center for Applied Genetic Technologies, University of Georgia, 111 Riverbend Road, Athens, GA 30602.
authors.forename: Stephanie A
authors.initials: SA
authors.lastname: Pearl
authors.affiliation: Center for Applied Genetic Technologies, University of Georgia, 111 Riverbend Road, Athens, GA 30602; Institute of Plant Breeding, Genetics and Genomics, University of Georgia, 111 Riverbend Road, Athens, GA 30602. Electronic address: sjackson@uga.edu.
authors.forename: Scott A
authors.initials: SA
authors.lastname: Jackson
mesh_terms: D015870:Gene Expression; D053263:Gene Regulatory Networks; D010641:Phenotype; D010944:Plants / Q000235:genetics*; D049490:Systems Biology