This paper describes the SZS ontologies that provide status values for precisely describing what is known or has been established about logical data. The ontology values are useful for describing existing logical data, and for automated reasoning software to describe their input and output. Standards for presenting the ontology values are also provided. 1

Computers as technical tools pervade modern science. Uniquely flexible devices, they can simulate any imaginable instrument, and programming has become a standard skill in many sciences such as physics and chemistry 1. Biologists realized the importance of computers only after The Web had popularized the “vending machine ” model of computation, where everything is expected to be available at the push of a button. As a result, the current generation of working biologists is not trained in programming and must instead rely upon programmers who are usually not trained in biology. Indeed, whole new fields, including “bioinformatics ” and “computational biology”, have grown up to fill this niche. 2 About 1996, armed only with training in computer science and cognitive science 3 I decided that I wanted to be a molecular biologist and work on cyanobacteria, a class of environmentally important marine photosynthetic bacteria. Fortuitously, at about that time a friend asked me to join his computational drug discovery start-up, which offered me both an excuse to learn some organic chemistry and biochemistry, and a path to the funding I would need to support myself as a lab volunteer. While commuting to that job

Personalization capabilities in computer applications attempt to better meet the needs of individuals. The more traditional and widespread paradigm in application design is that the user should adapt to the available application. This requires that the individual user's task be sliced and molded to fit the dimensions offered by an inflexible, monolithic application. It is desirable to have an application that can be shaped to fit each individual user's dynamic needs. However, it is important that this is done in an intuitive and unobtrusive way. In this thesis, we design and evaluate a personalizable application developed to aid life science researchers in their work. We designed the application in Haystack, a platform for developing semantic applications and user interfaces. The application gave the user flexibility in personalizing the way in which information is organized and displayed, while giving users access to the tools necessary to perform their tasks.

Akinetes are spore-like resting cells formed by certain filamentous cyanobacteria that have increased resistance to environmental stress. They can be found at low frequencies in dense cultures experiencing low light or phosphate limitation, but also form at high frequencies in a zwf mutant strain of Nostoc punctiforme following dark incubation in the presence of fructose. The wild-type strain is capable of facultative heterotrophic growth under these conditions and does not form akinetes. To identify genes associated with akinete development, differential display was used to amplify and compare cDNA from a wild-type and zwf mutant strain of N. punctiforme following a switch to dark heterotrophic conditions. Screening of candidate genes by reverse transcriptase real-time quantitative PCR and subsequent testing for akinetespecific expression using GFP transcriptional reporter plasmids lead to the identification of three novel akinete-expressed genes. The genes identified from the screening encoded for proteins homologous to an aminopeptidase (aapN), a zinc protease (hap) and an ATP-binding cassette (ABC)-type transporter (aet). Expression of hap was also increased in developing hormogonia, a transient type of differentiated filament capable of gliding motility. Transcriptional start sites for akinete-expressed genes were determined using random amplification of cDNA ends (RACE), and promoter regions were compared with orthologues in other filamentous cyanobacteria to identify putative regulatory sequences.

Abstract. Our work concerns the elucidation of the cancer (epi)genome, transcriptome and proteome to better understand the complex interplay between a cancer cell’s molecular state and its response to anti-cancer therapy. To study the problem, we have previously focused on data warehousing technologies and statistical data integration. In this paper, we present recent work on extending our analytical capabilities using Semantic Web technology. A key new component presented here is a SPARQL endpoint to our existing data warehouse. This endpoint allows the merging of observed quantitative data with existing data from semantic knowledge sources such as Gene Ontology (GO). We show how such variegated quantitative and functional data can be integrated and accessed in a universal manner using Semantic Web tools. We also demonstrate how Description Logic (DL) reasoning can be used to infer previously unstated conclusions from existing knowledge bases. As proof of concept, we illustrate the ability of our setup to answer complex queries on resistance of cancer cells to Decitabine, a demethylating agent.