Computational tools for the analysis of spatial patterns of gene expression in Common Lisp

Abstract

Scientific and technological advances in biotechnology have led to the determination of the sequence of the genomes of a growing number of organisms. Tools such as DNA microarrays offer the ability to determine the levels of expression of substantially all of the genes in a given genome in a single experiment, yet are limited to providing the levels of expression across an ensemble of cells, such as a particular organ or the entire organism. In order to understand the developmental roles of these genes, it is highly desirable not just to know if a given gene expressed, but in which tissues and at which times a given gene is expressed. Using high-throughput laboratory techniques we have constructed an atlas of spatial patterns of gene expression in Drosophila melanogaster imaginal discs. Building such an atlas requires a diverse array of computational techniques and, ideally, the atlas would be presented to the users not just in a static, browsable form, but in a computable form, along with tools to analyze the data contained in the atlas. To this end, we have developed a number of algorithms, tools and libraries, implemented in Common Lisp, to address problems such as matrix and image data representation, computer vision tasks, knowledge representation of the genes in the genome and maps of their global and spatial patterns of gene expression, and to query and analyze these data sets.