Bioinformatics Tools for Plant Genomics

The articles in this special issue reflect a convergence of developments in the fields of bioinformatics and plant genomics. Bioinformatics has its roots vaguely seated in the early 1980s, a time when personal computers began appearing in research laboratories and researchers began recognizing that those computers could be used as tools to organize, analyze and visualize their data. In the ensuing years bioinformatics tools began appearing at various sites and in countless laboratories throughout the world. These last efforts resulted in the development of many of the tools described in this special issue. Progress and interest in plant genomics have been accelerating since the time in late 2000 when the genome of Arabidopsis thaliana was published. Since then many genome sequencing projects have been undertaken that include poplar (Populus), grape (Vitis), the moss Physcomitrella, the biflagellate algae Chlamydomonas and several globally crucial crop plants such as corn (Maize) and rice (Oryza). However, as we have witnessed on numerous occasions, determining the sequence of a genome is only the first step toward understanding genome organization, gene structure, gene expression patterns, disease pathogenesis and a host of other features of both scientific and commercial interests. Computational tools of genomic annotation and comparative genomics must be applied to gain a useful understanding of any genome. In this special issue we present a collection of papers that together describe a powerful and impactful toolbox of applications and resources for plant genomic analysis. Among those articles you will find a description of research performed by the Mexican headquartered Generation Challenge Programme (GCP) which led to the GCP Platform (Bruskiewich et al.). This research support tool supports a number of data formats and web services and provides access to high performance computing facilities and platform-specific middleware collectively designed to support crop science research. Probably one of the most promising empirical tools for investigating gene expression developed in the last 15 or so years is that of microarray technology. While the technology has become commonplace, with tools for generating and hybridizing arrays available to all, the analysis of microarray-derived data has been challenging. Many laboratories have struggled not only with this challenge but also with the task of sorting through the plethora of analytical tools available in an effort to find the ones that may be best suited to their own work. In this issue there are two reviews by Page and Coulibaly which examine and describe …