Modeling plant mRNA poly(A) sites: Software design and implementation

作者：Ji Guoli^*; Wu Xiaohui; Zheng Jianti; Shen Yingjia; Lie Qingshun Quinn

来源：Journal of Computational and Theoretical Nanoscience, 2007, 4(7-8): 1365-1368.

DOI：10.1166/jctn.2007.025

• PASS
• polyadenylation
• poly(A) site
• GHMM
• prediction

A program known as Poly(A) Site Sleuth (PASS), that is presented here, has been developed to predict the poly(A) sites of plant messenger RNA. The algorithm is designed based on the Generalized Hidden Markov Model (GHMM) and the features of Arabidopsis genomic sequences and expressed sequence tags. Until recently, plant mRNA poly(A) sites are only determined from biological experiments. This is because there is little conservation of polyadenylation signals and complex alternative poly(A) site usage, which complicate the modeling of the gene expression process. Taking advantage of recent developments in the interdisciplinary fields of biology, mathematics and informatics, the PASS program has successfully applied a computer recognition model and algorithm to solve a biological problem.

• 出版日期2007-12
• 单位厦门大学