The mouse and human IGSF6 (DORA) genes map to the inflammatory bowel disease 1 locus and are embedded in an intron of a gene of unknown function.

We have previously characterized IGSF6 (DORA), a novel member of the immunoglobulin superfamily (IGSF) from human and rat expressed in dendritic and myeloid cells. Using a probe from the open reading frame of the rat cDNA, we isolated a cosmid which contains the entire mouse gene. By comparative analysis and reverse transcriptase polymerase chain reaction, we defined the intron/exon structure and the mRNA of the mouse gene and, with respect to human BAC clones, the human gene. The genes span 10 kb (mouse) and 12 kb (human), with six exons arranged in a manner similar to other members of the IGSF. All intron/exon boundaries follow the GT-AG rule. Expression of the mouse Igsf6 gene is restricted to cells of the immune system, particularly macrophages. Northern blot revealed a single mRNA of 2.5 kb, in contrast to the human gene which is expressed as two mRNAs of 1 and 2.5 kb. The human and mouse genes were localized to a locus associated with inflammatory bowel disease. Analysis of the flanking regions of the Igsf6 gene revealed the presence of an unrelated gene, transcribed from the opposite strand of the DNA and oriented such that the Igsf6 gene is encoded entirely within an intron. An identical organization is seen in human. This gene of unknown function is transcribed and processed, contains homologues in Caenorhabditis elegans and prokaryotes, and is expressed in most organs in the mouse.

A comparative analysis of multidimensional features of objects resembling sets of graphs

In the present paper, we introduce a notion of a style representing abstract, complex objects having characteristics that can be represented as structured objects. Furthermore, we provide some mathematical properties of such styles. As a main result, we present a novel approach to perform a meaningful comparative analysis of such styles by defining and using graph-theoretic measures. We compare two styles by comparing the underlying feature sets representing sets of graph structurally. To determine the structural similarity between the underlying graphs, we use graph similarity measures that are computationally efficient. More precisely, in order to compare styles, we map each feature set to a so-called median graph and compare the resulting median graphs. As an application, we perform an experimental study to compare special styles representing sets of undirected graphs and present numerical results thereof. (C) 2007 Elsevier Inc. All rights reserved.