http://www.j-biomed-discovery.com The latest research articles published by Journal of Biomedical Discovery and Collaboration 2009-02-13T00:00:00Z This is an RSS newsfeed from BioMed Central It is intended to be used with an RSS reader. For more information about RSS newsfeeds from BioMed Central, visit http://www.biomedcentral.com/info/about/rss/ Background: Current usability studies of bioinformatics tools suggest that tools for exploratory analysis support some tasks related to finding relationships of interest but not the deep causal insights necessary for formulating plausible and credible hypotheses. To better understand design requirements for gaining these causal insights in systems biology analyses a longitudinal field study of 15 biomedical researchers was conducted. Researchers interacted with the same protein-protein interaction tools to discover possible disease mechanisms for further experimentation. Results: Findings reveal patterns in scientists' exploratory and explanatory analysis and reveal that tools positively supported a number of well-structured query and analysis tasks. But for several of scientists' more complex, higher order ways of knowing and reasoning the tools did not offer adequate support. Results show that for a better fit with scientists' cognition for exploratory analysis systems biology tools need to better match scientists' processes for validating, for making a transition from classification to model-based reasoning, and for engaging in causal mental modelling. Conclusion: As the next great frontier in bioinformatics usability, tool designs for exploratory systems biology analysis need to move beyond the successes already achieved in supporting formulaic query and analysis tasks and now reduce current mismatches with several of scientists' higher order analytical practices. The implications of results for tool designs are discussed. http://www.j-biomed-discovery.com/content/4/1/2 Barbara Mirel Journal of Biomedical Discovery and Collaboration 2009, 4:2 2009-02-13T00:00:00Z doi:10.1186/1747-5333-4-2 Journal of Biomedical Discovery and Collaboration 1747-5333 4 2 2009-02-13T00:00:00Z XML Background: Biomedical scientists need to access figures to validate research facts and to formulate or to test novel research hypotheses. However, figures are difficult to comprehend without associated text (e.g., figure legend and other reference text). We are developing automated systems to extract the relevant explanatory information along with figures extracted from full text articles. Such systems could be very useful in improving figure retrieval and in reducing the workload of biomedical scientists, who otherwise have to retrieve and read the entire full-text journal article to determine which figures are relevant to their research. As a crucial step, we studied the importance of associated text in biomedical figure comprehension. Methods: Twenty subjects evaluated three figure-text combinations: figure+legend, figure+legend+title+abstract, and figure+full-text. Using a Likert scale, each subject scored each figure+text according to the extent to which the subject thought he/she understood the meaning of the figure and the confidence in providing the assigned score. Additionally, each subject entered a free text summary for each figure-text. We identified missing information using indicator words present within the text summaries. Both the Likert scores and the missing information were statistically analyzed for differences among the figure-text types. We also evaluated the quality of text summaries with the text-summarization evaluation method the ROUGE score. Results: Our results showed statistically significant differences in figure comprehension when varying levels of text were provided. When the full-text article is not available, presenting just the figure+legend left biomedical researchers lacking 39–68% of the information about a figure as compared to having complete figure comprehension; adding the title and abstract improved the situation, but still left biomedical researchers missing 30% of the information. When the full-text article is available, figure comprehension increased to 86–97%; this indicates that researchers felt that only 3–14% of the necessary information for full figure comprehension was missing when full text was available to them. Clearly there is information in the abstract and in the full text that biomedical scientists deem important for understanding the figures that appear in full-text biomedical articles. Conclusion: We conclude that the texts that appear in full-text biomedical articles are useful for understanding the meaning of a figure, and an effective figure-mining system needs to unlock the information beyond figure legend. Our work provides important guidance to the figure mining systems that extract information only from figure and figure legend. http://www.j-biomed-discovery.com/content/4/1/1 Hong Yu Shashank Agarwal Mark Johnston Aaron Cohen Journal of Biomedical Discovery and Collaboration 2009, 4:1 2009-01-06T00:00:00Z doi:10.1186/1747-5333-4-1 Journal of Biomedical Discovery and Collaboration 1747-5333 4 1 2009-01-06T00:00:00Z XML Background: The term blue skies research implies a freedom to carry out flexible, curiosity-driven research that leads to outcomes not envisaged at the outset. This research often challenges accepted thinking and introduces new fields of study. Science policy in the UK has given growing support for short-term goal-oriented scientific research projects, with pressure being applied on researchers to demonstrate the future application of their work. These policies carry the risk of restricting freedom, curbing research direction, and stifling rather than stimulating the creativity needed for scientific discovery. Methods: This study tracks the tortuous routes that led to three major discoveries in cardiology. It then investigates the constraints in current research, and opportunities that may be lost with existing funding processes, by interviewing selected scientists and fund providers for their views on curiosity-driven research and the freedom needed to allow science to flourish. The transcripts were analysed using a grounded theory approach to gather recurrent themes from the interviews. Results: The results from these interviews suggest that scientists often cannot predict the future applications of research. Constraints such as lack of scientific freedom, and a narrow focus on relevance and accountability were believed to stifle the discovery process. Although it was acknowledged that some research projects do need a clear and measurable framework, the interviewees saw a need for inquisitive, blue skies research to be managed in a different way. They provided examples of situations where money allocated to 'safe' funding was used for more innovative research. Conclusion: This sample of key UK scientists and grant providers acknowledge the importance of basic blue skies research. Yet the current evaluation process often requires that scientists predict their likely findings and estimate short-term impact, which does not permit freedom of research direction. There is a vital need for prominent scientists and for universities to help the media, the public, and policy makers to understand the importance of innovative thought along with the need for scientists to have the freedom to challenge accepted thinking. Encouraging an avenue for blue skies research could have immense influence over future scientific discoveries. http://www.j-biomed-discovery.com/content/3/1/3 Belinda Linden Journal of Biomedical Discovery and Collaboration 2008, 3:3 2008-02-29T00:00:00Z doi:10.1186/1747-5333-3-3 Journal of Biomedical Discovery and Collaboration 1747-5333 3 3 2008-02-29T00:00:00Z XML Background: PubMed is designed to provide rapid, comprehensive retrieval of papers that discuss a given topic. However, because PubMed does not organize the search output further, it is difficult for users to grasp an overview of the retrieved literature according to non-topical dimensions, to drill-down to find individual articles relevant to a particular individual's need, or to browse the collection. Results: In this paper, we present Anne O'Tate, a web-based tool that processes articles retrieved from PubMed and displays multiple aspects of the articles to the user, according to pre-defined categories such as the "most important" words found in titles or abstracts; topics; journals; authors; publication years; and affiliations. Clicking on a given item opens a new window that displays all papers that contain that item. One can navigate by drilling down through the categories progressively, e.g., one can first restrict the articles according to author name and then restrict that subset by affiliation. Alternatively, one can expand small sets of articles to display the most closely related articles. We also implemented a novel cluster-by-topic method that generates a concise set of topics covering most of the retrieved articles. Conclusion: Anne O'Tate is an integrated, generic tool for summarization, drill-down and browsing of PubMed search results that accommodates a wide range of biomedical users and needs. It can be accessed at 4. Peer review and editorial matters for this article were handled by Aaron Cohen. http://www.j-biomed-discovery.com/content/3/1/2 Neil Smalheiser Wei Zhou Vetle Torvik Journal of Biomedical Discovery and Collaboration 2008, 3:2 2008-02-15T00:00:00Z doi:10.1186/1747-5333-3-2 Journal of Biomedical Discovery and Collaboration 1747-5333 3 2 2008-02-15T00:00:00Z XML Background: Improved evaluation methodologies have been identified as a necessary prerequisite to the improvement of text mining theory and practice. This paper presents a publicly available framework that facilitates thorough, structured, and large-scale evaluations of text mining technologies. The extensibility of this framework and its ability to uncover system-wide characteristics by analyzing component parts as well as its usefulness for facilitating third-party application integration are demonstrated through examples in the biomedical domain. Results: Our evaluation framework was assembled using the Unstructured Information Management Architecture. It was used to analyze a set of gene mention identification systems involving 225 combinations of system, evaluation corpus, and correctness measure. Interactions between all three were found to affect the relative rankings of the systems. A second experiment evaluated gene normalization system performance using as input 4,097 combinations of gene mention systems and gene mention system-combining strategies. Gene mention system recall is shown to affect gene normalization system performance much more than does gene mention system precision, and high gene normalization performance is shown to be achievable with remarkably low levels of gene mention system precision. Conclusion: The software presented in this paper demonstrates the potential for novel discovery resulting from the structured evaluation of biomedical language processing systems, as well as the usefulness of such an evaluation framework for promoting collaboration between developers of biomedical language processing technologies. The code base is available as part of the BioNLP UIMA Component Repository on SourceForge.net. http://www.j-biomed-discovery.com/content/3/1/1 William Baumgartner K Cohen Lawrence Hunter Journal of Biomedical Discovery and Collaboration 2008, 3:1 2008-01-29T00:00:00Z doi:10.1186/1747-5333-3-1 Journal of Biomedical Discovery and Collaboration 1747-5333 3 1 2008-01-29T00:00:00Z XML Background: Biological organisms and their components are better conceived within categories based on similarity rather than on identity. Biologists routinely operate with similarity-based concepts such as "model organism" and "motif." There has been little exploration of the characteristics of the similarity-based categories that exist in biology. This study uses the case of the discovery and classification of zinc finger proteins to explore how biological categories based in similarity are represented. Results: The existence of a category of "zinc finger proteins" was based in 1) a lumpy gradient of similarity, 2) a link between function and structure, 3) establishment of a range of appearance across systems and organisms, and 4) an evolutionary locus as a historically based common-ground. Conclusion: More systematic application of the idea of similarity-based categorization might eliminate the assumption that biological characteristics can only contribute to narrow categorization of humans. It also raises possibilities for refining data-driven exploration efforts. http://www.j-biomed-discovery.com/content/2/1/5 Celeste Condit L. Bruce Railsback Journal of Biomedical Discovery and Collaboration 2007, 2:5 2007-10-03T00:00:00Z doi:10.1186/1747-5333-2-5 Journal of Biomedical Discovery and Collaboration 1747-5333 2 5 2007-10-03T00:00:00Z XML Background: Most biomedical corpora have not been used outside of the lab that created them, despite the fact that the availability of the gold-standard evaluation data that they provide is one of the rate-limiting factors for the progress of biomedical text mining. Data suggest that one major factor affecting the use of a corpus outside of its home laboratory is the format in which it is distributed. This paper tests the hypothesis that corpus refactoring – changing the format of a corpus without altering its semantics – is a feasible goal, namely that it can be accomplished with a semi-automatable process and in a time-effcient way. We used simple text processing methods and limited human validation to convert the Protein Design Group corpus into two new formats: WordFreak and embedded XML. We tracked the total time expended and the success rates of the automated steps. Results: The refactored corpus is available for download at the BioNLP SourceForge website http://bionlp.sourceforge.net. The total time expended was just over three person-weeks, consisting of about 102 hours of programming time (much of which is one-time development cost) and 20 hours of manual validation of automatic outputs. Additionally, the steps required to refactor any corpus are presented. Conclusion: We conclude that refactoring of publicly available corpora is a technically and economically feasible method for increasing the usage of data already available for evaluating biomedical language processing systems. http://www.j-biomed-discovery.com/content/2/1/4 Helen Johnson William Baumgartner Martin Krallinger K. Bretonnel Cohen Lawrence Hunter Journal of Biomedical Discovery and Collaboration 2007, 2:4 2007-09-13T00:00:00Z doi:10.1186/1747-5333-2-4 Journal of Biomedical Discovery and Collaboration 1747-5333 2 4 2007-09-13T00:00:00Z XML Nanotechnology research has lately been of intense interest because of its perceived potential for many diverse fields of science. Nanotechnology's tools have found application in diverse fields, from biology to device physics. By the 1990s, there was a concerted effort in the United States to develop a national initiative to promote such research. The success of this effort led to a significant influx of resources and interest in nanotechnology and nanobiotechnology and to the establishment of centralized research programs and facilities. Further government initiatives (at federal, state, and local levels) have firmly cemented these disciplines as 'big science,' with efforts increasingly concentrated at select laboratories and centers. In many respects, these trends mirror certain changes in academic science over the past twenty years, with a greater emphasis on applied science and research that can be more directly utilized for commercial applications.We also compare the National Nanotechnology Initiative and its successors to the Human Genome Project, another large-scale, government funded initiative. These precedents made acceptance of shifts in nanotechnology easier for researchers to accept, as they followed trends already established within most fields of science. Finally, these trends are examined in the design of technologies for detection and treatment of cancer, through the Alliance for Nanotechnology in Cancer initiative of the National Cancer Institute. Federal funding of these nanotechnology initiatives has allowed for expansion into diverse fields and the impetus for expanding the scope of research of several fields, especially biomedicine, though the ultimate utility and impact of all these efforts remains to be seen. http://www.j-biomed-discovery.com/content/2/1/3 Rajan Kulkarni Journal of Biomedical Discovery and Collaboration 2007, 2:3 2007-07-14T00:00:00Z doi:10.1186/1747-5333-2-3 Journal of Biomedical Discovery and Collaboration 1747-5333 2 3 2007-07-14T00:00:00Z XML Background: Collaborative efforts of physicians and basic scientists are often necessary in the investigation of complex disorders. Difficulties can arise, however, when large amounts of information need to reviewed. Advanced information retrieval can be beneficial in combining and reviewing data obtained from the various scientific fields. In this paper, a team of investigators with varying backgrounds has applied advanced information retrieval methods, in the form of text mining and entity relationship tools, to review the current literature, with the intention to generate new insights into the molecular mechanisms underlying a complex disorder. As an example of such a disorder the Complex Regional Pain Syndrome (CRPS) was chosen. CRPS is a painful and debilitating syndrome with a complex etiology that is still unraveled for a considerable part, resulting in suboptimal diagnosis and treatment. Results: A text mining based approach combined with a simple network analysis identified Nuclear Factor kappa B (NFκB) as a possible central mediator in both the initiation and progression of CRPS. Conclusion: The result shows the added value of a multidisciplinary approach combined with information retrieval in hypothesis discovery in biomedical research. The new hypothesis, which was derived in silico, provides a framework for further mechanistic studies into the underlying molecular mechanisms of CRPS and requires evaluation in clinical and epidemiological studies. http://www.j-biomed-discovery.com/content/2/1/2 Kristina Hettne Marissa de Mos Anke de Bruijn Marc Weeber Scott Boyer Erik van Mulligen Montserrat Cases Jordi Mestres Johan van der Lei Journal of Biomedical Discovery and Collaboration 2007, 2:2 2007-05-04T00:00:00Z doi:10.1186/1747-5333-2-2 Journal of Biomedical Discovery and Collaboration 1747-5333 2 2 2007-05-04T00:00:00Z XML Data management and integration are complicated and ongoing problems that will require commitment of resources and expertise from the various biological science communities. Primary components of successful cross-scale integration are smooth information management and migration from one context to another. We call for a broadening of the definition of bioinformatics and bioinformatics training to span biological disciplines and biological scales. Training programs are needed that educate a new kind of informatics professional, Biological Information Specialists, to work in collaboration with various discipline-specific research personnel. Biological Information Specialists are an extension of the informationist movement that began within library and information science (LIS) over 30 years ago as a professional position to fill a gap in clinical medicine. These professionals will help advance science by improving access to scientific information and by freeing scientists who are not interested in data management to concentrate on their science. http://www.j-biomed-discovery.com/content/2/1/1 P. Bryan Heidorn Carole Palmer Dan Wright Journal of Biomedical Discovery and Collaboration 2007, 2:1 2007-02-12T00:00:00Z doi:10.1186/1747-5333-2-1 Journal of Biomedical Discovery and Collaboration 1747-5333 2 1 2007-02-12T00:00:00Z XML