Introduction to semantic e-Science in biomedicine

The Semantic Web technologies provide enhanced capabilities that allow data and the meaning of the data to be shared and reused across application, enterprise, and community boundaries, better enabling integrative research and more effective knowledge discovery. This special issue is intended to give an introduction of the state-of-the-art of Semantic Web technologies and describe how such technologies would be used to build the e-Science infrastructure for biomedical communities. Six papers have been selected and included, featuring different approaches and experiences in a variety of biomedical domains

Visualizing the information space of hypermedia systems

Ph.D.James D. Fole

DISCOVERING BIOMEDICAL RELATIONS UTILIZING THE WORLD-WIDE WEB

To crate a Semantic Web for Life Sciences discovering relations between biomedical entities is essential. Journals and conference proceedings represent the dominant mechanisms of reporting newly discovered biomedical interactions. The unstructured nature of such publications makes it difficult to utilize data mining or knowledge discovery techniques to automatically incorporate knowledge from these publications into the ontologies. On the other hand, since biomedical information is growing explosively, it is difficult to have human curators manually extract all the information from literature. In this paper we present techniques to automatically discover biomedical relations from the World-wide Web. For this purpose we retrieve relevant information from Web Search engines using various lexicosyntactic patterns as queries. Experiments are presented to show the usefulness of our techniques. 1

DISCOVERING BIOMEDICAL RELATIONS UTILIZING

To crate a Semantic Web for Life Sciences discovering relations between biomedical entities is essential. Journals and conference proceedings represent the dominant mechanisms of reporting newly discovered biomedical interactions. The unstructured nature of such publications makes it difficult to utilize data mining or knowledge discovery techniques to automatically incorporate knowledge from these publications into the ontologies. On the other hand, since biomedical information is growing explosively, it is difficult to have human curators manually extract all the information from literature. In this paper we present techniques to automatically discover biomedical relations from the World-wide Web. For this purpose we retrieve relevant information from Web Search engines using various lexicosyntactic patterns as queries. Experiments are presented to show the usefulness of our techniques. 1

Some relatives of the Catalan sequence

We study a family of sequences $c_n(a_2,\ldots,a_r)$, where $r\ge2$ and $a_2,\ldots,a_r$ are real parameters. We find a sufficient condition for positive definiteness of the sequence $c_n(a_2,\ldots,a_r)$ and check several examples from OEIS. We also study relations of these sequences with the free and monotonic convolution

Visualizing the World-Wide Web with the Navigational View Builder

Overview diagrams are one of the best tools for orientation and navigation in hypermedia systems. However, constructing effective overview diagrams is a challenging task. This paper describes the Navigational View Builder, a tool which allows the user to interactively create useful visualizations of the information space. It uses four strategies to form effective views. These are binding, clustering, filtering and hierarchization. These strategies use a combination of structural and content analysis of the underlying space for forming the visualizations. This paper discusses these strategies and shows how they can be applied for forming visualizations for the World-Wide Web

Object-Oriented Schema Extension and Abstraction

An algorithm is presented that abstracts out the "largest" common substructure of two given objectoriented class structures. This abstraction algorithm is based on two concepts: (1) a mathematical formulation of extension for class structures containing part-of and inheritance relationships, and (2) a definition of similarity on the class level. The algorithm shows how class structures can be optimized with respect to the extension relation, and how it can be used to abstract out a candidate parameterized class structure. The algorithm has been implemented as a schema transformation and design tool in the Demeter System