Electronic libraries and electronic librarians: Who does what in a national electronic community

This talk will have two parts: First, I'm going to describe very briefly what this new kind of library technology is like through a discussion of the Worm Community System (WCS), why it is going to be very important, and why it will involve a lot of money. What I want to emphasize at the start is that while WCS may seem like an esoteric research project, in fact it is one of the flagship information projects funded by the National Science Foundation. In addition, the National Information Infrastructure Act looms in the immediate future, authorizing an enormous amount of money to be spent in the development of digital libraries in specialized areas. Digital libraries will require information systems like WCS. This project has become a national model of this new kind of information system, but its primary content is really just a special collection, in the same sense you already know. It is an important national effort, but there will be lots of other efforts like this in many different subject areas. Second, I'm going to discuss in more detail what kinds of people are required to do this kind of activity. The roles range from traditional librarians all the way to systems architects. Similarly, the roles range from those that involve no computer knowledge at all to those that involve very intensive computing. My expectation is that people who call themselves "librarians" in the foreseeable future will actually span this entire range, even though now they are significantly skewed towards the traditional end.published or submitted for publicatio

On the Representation and Use of Semantic Categories: A Survey and Prospectus

This report describes research conducted at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the Laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract number N00014-75-C-0643.This paper is intended as a brief introduction to several issues concerning semantic categories. These are the everyday, factual groupings of world knowledge according to some similarity in characteristics. Some psychological data concerning the structure, formation, and use of categories is surveyed. Then several psychological models (set-theoretic and network) are considered. Various artificial intelligence representations (concerning the symbol mapping and recognition problems) dealing with similar issues are also reviewed. It is argued that these data and representations approach semantic categories at too abstract a level and a set of guidelines which may be helpful in constructing a microworld are given.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

Identifying overrepresented concepts in gene lists from literature: a statistical approach based on Poisson mixture model

<p>Abstract</p> <p>Background</p> <p>Large-scale genomic studies often identify large gene lists, for example, the genes sharing the same expression patterns. The interpretation of these gene lists is generally achieved by extracting concepts overrepresented in the gene lists. This analysis often depends on manual annotation of genes based on controlled vocabularies, in particular, Gene Ontology (GO). However, the annotation of genes is a labor-intensive process; and the vocabularies are generally incomplete, leaving some important biological domains inadequately covered.</p> <p>Results</p> <p>We propose a statistical method that uses the primary literature, i.e. free-text, as the source to perform overrepresentation analysis. The method is based on a statistical framework of mixture model and addresses the methodological flaws in several existing programs. We implemented this method within a literature mining system, BeeSpace, taking advantage of its analysis environment and added features that facilitate the interactive analysis of gene sets. Through experimentation with several datasets, we showed that our program can effectively summarize the important conceptual themes of large gene sets, even when traditional GO-based analysis does not yield informative results.</p> <p>Conclusions</p> <p>We conclude that the current work will provide biologists with a tool that effectively complements the existing ones for overrepresentation analysis from genomic experiments. Our program, Genelist Analyzer, is freely available at: <url>http://workerbee.igb.uiuc.edu:8080/BeeSpace/Search.jsp</url></p

Ultralow-threshold, continuous-wave upconverting lasing from subwavelength plasmons.

Miniaturized lasers are an emerging platform for generating coherent light for quantum photonics, in vivo cellular imaging, solid-state lighting and fast three-dimensional sensing in smartphones1-3. Continuous-wave lasing at room temperature is critical for integration with opto-electronic devices and optimal modulation of optical interactions4,5. Plasmonic nanocavities integrated with gain can generate coherent light at subwavelength scales6-9, beyond the diffraction limit that constrains mode volumes in dielectric cavities such as semiconducting nanowires10,11. However, insufficient gain with respect to losses and thermal instabilities in nanocavities has limited all nanoscale lasers to pulsed pump sources and/or low-temperature operation6-9,12-15. Here, we show continuous-wave upconverting lasing at room temperature with record-low thresholds and high photostability from subwavelength plasmons. We achieve selective, single-mode lasing from Yb3+/Er3+-co-doped upconverting nanoparticles conformally coated on Ag nanopillar arrays that support a single, sharp lattice plasmon cavity mode and greater than wavelength λ/20 field confinement in the vertical dimension. The intense electromagnetic near-fields localized in the vicinity of the nanopillars result in a threshold of 70 W cm-2, orders of magnitude lower than other small lasers. Our plasmon-nanoarray upconverting lasers provide directional, ultra-stable output at visible frequencies under near-infrared pumping, even after six hours of constant operation, which offers prospects in previously unrealizable applications of coherent nanoscale light

BeeSpace Navigator: exploratory analysis of gene function using semantic indexing of biological literature

With the rapid decrease in cost of genome sequencing, the classification of gene function is becoming a primary problem. Such classification has been performed by human curators who read biological literature to extract evidence. BeeSpace Navigator is a prototype software for exploratory analysis of gene function using biological literature. The software supports an automatic analogue of the curator process to extract functions, with a simple interface intended for all biologists. Since extraction is done on selected collections that are semantically indexed into conceptual spaces, the curation can be task specific. Biological literature containing references to gene lists from expression experiments can be analyzed to extract concepts that are computational equivalents of a classification such as Gene Ontology, yielding discriminating concepts that differentiate gene mentions from other mentions. The functions of individual genes can be summarized from sentences in biological literature, to produce results resembling a model organism database entry that is automatically computed. Statistical frequency analysis based on literature phrase extraction generates offline semantic indexes to support these gene function services. The website with BeeSpace Navigator is free and open to all; there is no login requirement at www.beespace.illinois.edu for version 4. Materials from the 2010 BeeSpace Software Training Workshop are available at www.beespace.illinois.edu/bstwmaterials.php