Context-aware visual exploration of molecular databases

Facilitating the visual exploration of scientific data has received increasing attention in the past decade or so. Especially in life science related application areas the amount of available data has grown at a breath taking pace. In this paper we describe an approach that allows for visual inspection of large collections of molecular compounds. In contrast to classical visualizations of such spaces we incorporate a specific focus of analysis, for example the outcome of a biological experiment such as high throughout screening results. The presented method uses this experimental data to select molecular fragments of the underlying molecules that have interesting properties and uses the resulting space to generate a two dimensional map based on a singular value decomposition algorithm and a self organizing map. Experiments on real datasets show that the resulting visual landscape groups molecules of similar chemical properties in densely connected regions.

Soft topographic map for clustering and classification of bacteria

In this work a new method for clustering and building a topographic representation of a bacteria taxonomy is presented. The method is based on the analysis of stable parts of the genome, the so-called “housekeeping genes”. The proposed method generates topographic maps of the bacteria taxonomy, where relations among different type strains can be visually inspected and verified. Two well known DNA alignement algorithms are applied to the genomic sequences. Topographic maps are optimized to represent the similarity among the sequences according to their evolutionary distances. The experimental analysis is carried out on 147 type strains of the Gammaprotebacteria class by means of the 16S rRNA housekeeping gene. Complete sequences of the gene have been retrieved from the NCBI public database. In the experimental tests the maps show clusters of homologous type strains and present some singular cases potentially due to incorrect classification or erroneous annotations in the database.

GIS in the cloud: implementing a web map service on Google App Engine

Many producers of geographic information are now disseminating their data using open web service protocols, notably those published by the Open Geospatial Consortium. There are many challenges inherent in running robust and reliable services at reasonable cost. Cloud computing provides a new kind of scalable infrastructure that could address many of these challenges. In this study we implement a Web Map Service for raster imagery within the Google App Engine environment. We discuss the challenges of developing GIS applications within this framework and the performance characteristics of the implementation. Results show that the application scales well to multiple simultaneous users and performance will be adequate for many applications, although concerns remain over issues such as latency spikes. We discuss the feasibility of implementing services within the free usage quotas of Google App Engine and the possibility of extending the approaches in this paper to other GIS applications.

An enhanced microsatellite map of diploid Fragaria

A total of 45 microsatellites (SSRs) were developed for mapping in Fragaria. They included 31 newly isolated codominant genomic SSRs from F. nubicola and a further 14 SSRs, derived from an expressed sequence tagged library (EST-SSRs) of the cultivated strawberry, F. × ananassa. These, and an additional 64 previously characterised but unmapped SSRs and EST-SSRs, were scored in the diploid Fragaria interspecific F2 mapping population (FV×FN) derived from a cross between F. vesca 815 and F. nubicola 601. The cosegregation data of these 109 SSRs, and of 73 previously mapped molecular markers, were used to elaborate an enhanced linkage map. The map is composed of 182 molecular markers (175 microsatellites, six gene specific markers and one sequence-characterised amplified region) and spans 424 cM over seven linkage groups. The average marker spacing is 2.3 cM/marker and the map now contains just eight gaps longer than 10 cM. The transferability of the new SSR markers to the cultivated strawberry was demonstrated using eight cultivars. Because of the transferable nature of these markers, the map produced will provide a useful reference framework for the development of linkage maps of the cultivated strawberry and for the development of other key resources for Fragaria such as a physical map. In addition, the map now provides a framework upon which to place transferable markers, such as genes of known function, for comparative mapping purposes within Rosaceae.

A genetic linkage map of microsatellite, gene-specific and morphological markers in diploid Fragaria

Diploid Fragaria provide a potential model for genomic studies in the Rosaceae. To develop a genetic linkage map of diploid Fragaria, we scored 78 markers (68 microsatellites, one sequence-characterised amplified region, six gene-specific markers and three morphological traits) in an interspecific F2 population of 94 plants generated from a cross of F.vesca f. semperflorens × F. nubicola. Co-segregation analysis arranged 76 markers into seven discrete linkage groups covering 448 cM, with linkage group sizes ranging from 100.3 cM to 22.9 cM. Marker coverage was generally good; however some clustering of markers was observed on six of the seven linkage groups. Segregation distortion was observed at a high proportion of loci (54%), which could reflect the interspecific nature of the progeny and, in some cases, the self-incompatibility of F. nubicola. Such distortion may also account for some of the marker clustering observed in the map. One of the morphological markers, pale-green leaf (pg) has not previously been mapped in Fragaria and was located to the mid-point of linkage group VI. The transferable nature of the markers used in this study means that the map will be ideal for use as a framework for additional marker incorporation aimed at enhancing and resolving map coverage of the diploid Fragaria genome. The map also provides a sound basis for linkage map transfer to the cultivated octoploid strawberry.

Interactions of decay-accelerating factor (DAF) with haemagglutinating human enteroviruses: utilizing variation in primate DAF to map virus binding sites

A cellular receptor for the haemagglutinating enteroviruses (HEV), and the protein that mediates haemagglutination, is the membrane complement regulatory protein decay accelerating factor (DAF; CD55). Although primate DAF is highly conserved, significant differences exist to enable cell lines derived from primates to be utilized for the characterization of the DAF binding phenotype of human enteroviruses. Thus, several distinct DAF-binding phenotypes of a selection of HEVs (viz. coxsackievirus A21 and echoviruses 6, 7, 11-13, 29) were identified from binding and infection assays using a panel of primate cells derived from human, orang-utan, African Green monkey and baboon tissues. These studies complement our recent determination of the crystal structure of SCR(34) of human DAF [Williams, P., Chaudhry, Y., Goodfellow, I. G., Billington, J., Powell, R., Spiller, O. B., Evans, D. J. & Lea, S. (2003). J Biol Chem 278, 10691-10696] and have enabled us to better map the regions of DAF with which enteroviruses interact and, in certain cases, predict specific virus-receptor contacts.

Semi-automatic annotation and retrieval of visual content using the topic map technology

There are still major challenges in the area of automatic indexing and retrieval of multimedia content data for very large multimedia content corpora. Current indexing and retrieval applications still use keywords to index multimedia content and those keywords usually do not provide any knowledge about the semantic content of the data. With the increasing amount of multimedia content, it is inefficient to continue with this approach. In this paper, we describe the project DREAM, which addresses such challenges by proposing a new framework for semi-automatic annotation and retrieval of multimedia based on the semantic content. The framework uses the Topic Map Technology, as a tool to model the knowledge automatically extracted from the multimedia content using an Automatic Labelling Engine. We describe how we acquire knowledge from the content and represent this knowledge using the support of NLP to automatically generate Topic Maps. The framework is described in the context of film post-production.

Evolving features-algorithms knowledge map to support NIDS data intelligence and learning loop architecting – a generalised approach to NIDS pattern feature space knowledge processing

This paper describes a proposed new approach to the Computer Network Security Intrusion Detection Systems (NIDS) application domain knowledge processing focused on a topic map technology-enabled representation of features of the threat pattern space as well as the knowledge of situated efficacy of alternative candidate algorithms for pattern recognition within the NIDS domain. Thus an integrative knowledge representation framework for virtualisation, data intelligence and learning loop architecting in the NIDS domain is described together with specific aspects of its deployment.