We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

The Web-based software tool Genevestigator provides powerful tools for biologists to explore gene expression across a wide variety of biological contexts. Its first releases, however, were limited by the scaling ability of the system architecture, multiorganism data storage and analysis capability, and availability of computationally intensive analysis methods. Genevestigator V3 is a novel meta-analysis system resulting from new algorithmic and software development using a client/server architecture, large-scale manual curation and quality control of microarray data for several organisms, and curation of pathway data for mouse and Arabidopsis. In addition to improved querying features, Genevestigator V3 provides new tools to analyze the expression of genes in many different contexts, to identify biomarker genes, to cluster genes into expression modules, and to model expression responses in the context of metabolic and regulatory networks. Being a reference expression database with user-friendly tools, Genevestigator V3 facilitates discovery research and hypothesis validation.

/pdf/genevestigator-v3-a-reference-expression-database-for-the-14oh277j5j.pdf

Genevestigator v3: a reference expression database for the meta-analysis of transcriptomes.

Sugar efflux transporters are essential for the maintenance of animal blood glucose levels, plant nectar production, and plant seed and pollen development. Despite broad biological importance, the identity of sugar efflux transporters has remained elusive. Using optical glucose sensors, we identified a new class of sugar transporters, named SWEETs, and show that at least six out of seventeen Arabidopsis, two out of over twenty rice and two out of seven homologues in Caenorhabditis elegans, and the single copy human protein, mediate glucose transport. Arabidopsis SWEET8 is essential for pollen viability, and the rice homologues SWEET11 and SWEET14 are specifically exploited by bacterial pathogens for virulence by means of direct binding of a bacterial effector to the SWEET promoter. Bacterial symbionts and fungal and bacterial pathogens induce the expression of different SWEET genes, indicating that the sugar efflux function of SWEET transporters is probably targeted by pathogens and symbionts for nutritional gain. The metazoan homologues may be involved in sugar efflux from intestinal, liver, epididymis and mammary cells.

/pdf/sugar-transporters-for-intercellular-exchange-and-nutrition-54v09mfrcb.pdf

Sugar transporters for intercellular exchange and nutrition of pathogens

https://eprints.cs.univie.ac.at/3231/1/0-S1874939911001787-main.pdf

The plant heat stress transcription factor (Hsf) family: structure, function and evolution.

Plant hormones are small molecules that regulate plant growth and development, as well as responses to changing environmental conditions. By modifying the production, distribution or signal transduction of these hormones, plants are able to regulate and coordinate both growth and/or stress tolerance to promote survival or escape from environmental stress. A central role for the gibberellin (GA) class of growth hormones in the response to abiotic stress is becoming increasingly evident. Reduction of GA levels and signalling has been shown to contribute to plant growth restriction on exposure to several stresses, including cold, salt and osmotic stress. Conversely, increased GA biosynthesis and signalling promote growth in plant escape responses to shading and submergence. In several cases, GA signalling has also been linked to stress tolerance. The transcriptional regulation of GA metabolism appears to be a major point of regulation of the GA pathway, while emerging evidence for interaction of the GA-signalling molecule DELLA with components of the signalling pathway for the stress hormone jasmonic acid suggests additional mechanisms by which GA signalling may integrate multiple hormone signalling pathways in the response to stress. Here, we review the evidence for the role of GA in these processes, and the regulation of the GA signalling pathway on exposure to abiotic stress. The potential mechanisms by which GA signalling modulates stress tolerance are also discussed.

/pdf/the-role-of-gibberellin-signalling-in-plant-responses-to-9wuqxdfvgf.pdf

The role of gibberellin signalling in plant responses to abiotic stress

Background
RT-qPCR is a sensitive and increasingly used method for gene expression quantification. To normalize RT-qPCR measurements between samples, most laboratories use endogenous reference genes as internal controls. There is increasing evidence, however, that the expression of commonly used reference genes can vary significantly in certain contexts.

/pdf/refgenes-identification-of-reliable-and-condition-specific-4rwaapzcba.pdf

RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization

https://www.gene-quantification.de/zimmermann-genevestigator-2008.pdf

Genevestigator Transcriptome Meta-Analysis and Biomarker Search Using Rice and Barley Gene Expression Databases

Background
Gene function analysis often requires a complex and laborious sequence of laboratory and computer-based experiments. Choosing an effective experimental design generally results from hypotheses derived from prior knowledge or experimentation. Knowledge obtained from meta-analyzing compendia of expression data with annotation libraries can provide significant clues in understanding gene and network function, resulting in better hypotheses that can be tested in the laboratory.

/pdf/web-based-analysis-of-the-mouse-transcriptome-using-29rafg01ap.pdf

Web-based analysis of the mouse transcriptome using Genevestigator.

Reference datasets are often used to compare, interpret or validate experimental data and analytical methods. In the field of gene expression, several reference datasets have been published. Typically, they consist of individual baseline or spike-in experiments carried out in a single laboratory and representing a particular set of conditions. Here, we describe a new type of standardized datasets representative for the spatial and temporal dimensions of gene expression. They result from integrating expression data from a large number of globally normalized and quality controlled public experiments. Expression data is aggregated by anatomical part or stage of development to yield a representative transcriptome for each category. For example, we created a genome-wide expression dataset representing the FDA tissue panel across 35 tissue types. The proposed datasets were created for human and several model organisms and are publicly available at http://www.expressiondata.org
 .

/pdf/expressiondata-a-public-resource-of-high-quality-curated-3f7p5wcj2d.pdf

ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions

Tomas Hruz

Papers

Genevestigator v3: a reference expression database for the meta-analysis of transcriptomes.

RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization

Genevestigator Transcriptome Meta-Analysis and Biomarker Search Using Rice and Barley Gene Expression Databases

Web-based analysis of the mouse transcriptome using Genevestigator.

ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions