title: A computational algorithm for functional clustering of proteome dynamics during development.
abstract: Phenotypic traits, such as seed development, are a consequence of complex biochemical interactions among genes, proteins and metabolites, but the underlying mechanisms that operate in a coordinated and sequential manner remain elusive. Here, we address this issue by developing a computational algorithm to monitor proteome changes during the course of trait development. The algorithm is built within the mixture-model framework in which each mixture component is modeled by a specific group of proteins that display a similar temporal pattern of expression in trait development. A nonparametric approach based on Legendre orthogonal polynomials was used to fit dynamic changes of protein expression, increasing the power and flexibility of protein clustering. By analyzing a dataset of proteomic dynamics during early embryogenesis of the Chinese fir, the algorithm has successfully identified several distinct types of proteins that coordinate with each other to determine seed development in this forest tree commercially and environmentally important to China. The algorithm will find its immediate applications for the characterization of mechanistic underpinnings for any other biological processes in which protein abundance plays a key role.
authors: Center for Statistical Genetics, Pennsylvania State University, Hershey, PA 17033, USA.
authors: Yaqun
authors: Y
authors: Wang
authors: Center for Statistical Genetics, Pennsylvania State University, Hershey, PA 17033, USA.
authors: Ningtao
authors: N
authors: Wang
authors: Center for Statistical Genetics, Pennsylvania State University, Hershey, PA 17033, USA.
authors: Han
authors: H
authors: Hao
authors: Center for Computational Biology, Beijing Forestry University, Beijing 100083, China.
authors: Yunqian
authors: Y
authors: Guo
authors: Key Laboratory of Forest Genetics and Biotechnology, Nanjing Forestry University, Nanjing 210037, China.
authors: Yan
authors: Y
authors: Zhen
authors: Key Laboratory of Forest Genetics and Biotechnology, Nanjing Forestry University, Nanjing 210037, China.
authors: Jisen
authors: J
authors: Shi
authors: Center for Statistical Genetics, Pennsylvania State University, Hershey, PA 17033, USA.
authors: Rongling
authors: R
authors: Wu
keywords: Dynamic proteomics; Forest tree.; Functional clustering; Seed development; Unsupervised analysis