Pages: pp. 273-273
Advanced algorithms can help to identify functional relationships of genes in a biological process, discovery sequence, and structural similarities and provide insights into the regulatory mechanism in bioinformatics. In this special section, three papers in their significantly extended versions were selected from the papers presented at the Tenth Asia Pacific Bioinformatics Conference (APBC2012). These papers have shown great cooperation and conscientious consideration throughout the challenging bioinformatics experiments.
In “Chain-RNA: A Comparative ncRNA Search Tool Based on the Two-Dimensional Chain Algorithm,” Jikai Lei, Prapaporn Techa-angkoon, and Yanni Sun introduced a new de novo ncRNA search method and its implementation called chain-RNA. They formulated stem alignment as an extended 2D chain problem and utilized existing chain algorithms. The experimental results show that chain-RNA has better tradeoff between sensitivity and false positive rate in ncRNA prediction than conventional sequence similarity search tools and is more time competent than structural alignment tools.
In “Rough-Fuzzy Clustering for Grouping Functionally Similar Genes from Microarray Data,” Pradipta Maji and Sushmita Paul proposed an efficient method to select initial prototypes of different gene clusters, which enables the proposed c-means algorithm to converge to an optimum or near optimum solution and helps to discover coexpressed gene clusters. They developed a new gene clustering algorithm, which integrates judiciously c-means algorithm, rough sets, and probabilistic and possibilistic memberships of fuzzy sets. In this paper, the effectiveness of the proposed algorithm is established.
In “Computational Reconstruction of Transcriptional Relationships from ChIP-Chip Data,” Ngoc Tu Le, Tu Bao Ho, and Bich Hai Ho developed a method to reconstruct a Bayesian network (BN) model representing functional relationships among various transcriptional components. The resulting network model showed that transcriptional components positively influence each other. Along with them, GTFs, Mediator, and CRCs play critical roles in regulating the outcome of the whole process. Their process can also be extended to recreate more accurate model as data on other aspects of transcription become available. A few new functional relationships were also recommended, which may carry insights into regulatory mechanism and transcriptional regulation.
Yi-Ping Phoebe Chen