Linking genes to literature: text mining, information extraction, and retrieval applications for biology

Efficient access to information contained in online scientific literature collections is essential for life science research, playing a crucial role from the initial stage of experiment planning to the final interpretation and communication of the results. The biological literature also constitutes the main information source for manual literature curation used by expert-curated databases. Following the increasing popularity of web-based applications for analyzing biological data, new text-mining and information extraction strategies are being implemented. These systems exploit existing regularities in natural language to extract biologically relevant information from electronic texts automatically. The aim of the BioCreative challenge is to promote the development of such tools and to provide insight into their performance. This review presents a general introduction to the main characteristics and applications of currently available text-mining systems for life sciences in terms of the following: the type of biological information demands being addressed; the level of information granularity of both user queries and results; and the features and methods commonly exploited by these applications. The current trend in biomedical text mining points toward an increasing diversification in terms of application types and techniques, together with integration of domain-specific resources such as ontologies. Additional descriptions of some of the systems discussed here are available on the internet

Architectural Paint Research and the Archaeology of Buildings

Architectural Paint Research (APR) is the archaeological study of interior and exterior applied decoration. Over time, applied layers of paint and other decorative finishes build-up on the surface of a built structure, encapsulating microscopic deposits of material evidence. This evidence can be used to inform the phase dating of a structure, or illuminate the historic function of a space. It can challenge preconceived ideas of how specific areas were decorated, and track the changes in aesthetics over time. It can identify when architects’ ideologies have been balanced by practical considerations. It can provide an insight into the intangible and ephemeral atmosphere that decoration gives to a room. Finally, it can examine the dirt trapped between layers of decoration and thus categorize the physical environmental conditions that surrounded a building at varying points in its history. Although used in the commercial heritage and conservation sectors, Architectural Paint Research is almost completely unknown to building archaeologists. This article aims to introduce APR to a new audience, and argues that is an invaluable tool in the archaeological interpretation of buildings

Microplanning with Communicative Intentions: The SPUD System

The process of microplanning in Natural Language Generation (NLG) encompasses a range of problems in which a generator must bridge underlying domain-specific representations and general linguistic representations. These problems include constructing linguistic referring expressions to identify domain objects, selecting lexical items to express domain concepts, and using complex linguistic constructions to concisely convey related domain facts. In this paper, we argue that such problems are best solved through a uniform, comprehensive, declarative process. In our approach, the generator directly explores a search space for utterances described by a linguistic grammar. At each stage of search, the generator uses a model of interpretation, which characterizes the potential links between the utterance and the domain and context, to assess its progress in conveying domain-specific representations. We further address the challenges for implementation and knowledge representation in this approach. We show how to implement this approach effectively by using the lexicalized tree-adjoining grammar formalism (LTAG) to connect structure to meaning and using modal logic programming to connect meaning to context. We articulate a detailed methodology for designing grammatical and conceptua