http://www.j-biomed-discovery.com The most accessed 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/ The network model of innovation widely adopted among researchers in the economics of science and technology posits relatively porous boundaries between firms and academic research programs and a bi-directional flow of inventions, personnel, and tacit knowledge between sites of university and industry innovation. Moreover, the model suggests that these bi-directional flows should be considered as mutual stimulation of research and invention in both industry and academe, operating as a positive feedback loop. One side of this bi-directional flow – namely; the flow of inventions into industry through the licensing of university-based technologies – has been well studied; but the reverse phenomenon of the stimulation of university research through the absorption of new directions emanating from industry has yet to be investigated in much detail. We discuss the role of federal funding of academic research in the microarray field, and the multiple pathways through which federally supported development of commercial microarray technologies have transformed core academic research fields.Results and conclusionOur study confirms the picture put forward by several scholars that the open character of networked economies is what makes them truly innovative. In an open system innovations emerge from the network. The emergence and diffusion of microarray technologies we have traced here provides an excellent example of an open system of innovation in action. Whether they originated in a startup company environment that operated like a think-tank, such as Affymax, the research labs of a large firm, such as Agilent, or within a research university, the inventors we have followed drew heavily on knowledge resources from all parts of the network in bringing microarray platforms to light.Federal funding for high-tech startups and new industrial development was important at several phases in the early history of microarrays, and federal funding of academic researchers using microarrays was fundamental to transforming the research agendas of several fields within academe. The typical story told about the role of federal funding emphasizes the spillovers from federally funded academic research to industry. Our study shows that the knowledge spillovers worked both ways, with federal funding of non-university research providing the impetus for reshaping the research agendas of several academic fields. http://www.j-biomed-discovery.com/content/1/1/11 Timothy Lenoir Eric Giannella Journal of Biomedical Discovery and Collaboration 2006, 1:11 2006-08-22T00:00:00Z doi:10.1186/1747-5333-1-11 Journal of Biomedical Discovery and Collaboration 1747-5333 1 11 2006-08-22T00:00:00Z XML IntroductionPolymerase chain reaction (PCR) was a seminal genomic technology discovered, developed, and patented in an industry setting. Since the first of its core patents expired in March, 2005, we are in a position to view the entire lifespan of the patent, examining how the intellectual property rights have impacted its use in the biomedical community. Given its essential role in the world of molecular biology and its commercial success, the technology can serve as a case study for evaluating the effects of patenting biological research tools on biomedical research.Case descriptionFollowing its discovery, the technique was subjected to two years of in-house development, during which issues of inventorship and publishing/patenting strategies caused friction between members of the development team. Some have feared that this delay impeded subsequent research and may have been due to trade secrecy or the desire for obtaining lucrative intellectual property rights. However, our analysis of the history indicates that the main reasons for the delay were benign and were primarily due to difficulties in perfecting the PCR technique. Following this initial development period, the technology was made widely available, but was subject to strict licensing terms and patent protection, leading to an extensive litigation history.Discussion and evaluationPCR has earned approximately $2 billion in royalties for the various rights-holders while also becoming an essential research tool. However, using citation trend analysis, we are able to see that PCR's patented status did not preclude it from being adopted in a similar manner as other non-patented genomic research tools (specifically, pBR322 cloning vector and Maxam-Gilbert sequencing). Conclusion: Despite the heavy patent protection and rigid licensing schemes, PCR seems to have disseminated so widely because of the practices of the corporate entities which have controlled these patents, namely through the use of business partnerships and broad corporate licensing, adaptive licensing strategies, and a "rational forbearance" from suing researchers for patent infringement. While far from definitive, our analysis seems to suggest that, at least in the case of PCR, patenting of genomic research tools need not impede their dissemination, if the technology is made available through appropriate business practices. http://www.j-biomed-discovery.com/content/1/1/7 Joe Fore Ilse Wiechers Robert Cook-Deegan Journal of Biomedical Discovery and Collaboration 2006, 1:7 2006-07-03T00:00:00Z doi:10.1186/1747-5333-1-7 Journal of Biomedical Discovery and Collaboration 1747-5333 1 7 2006-07-03T00:00:00Z 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 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: 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 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 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 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 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: Annotation of proteins with gene ontology (GO) terms is ongoing work and a complex task. Manual GO annotation is precise and precious, but it is time-consuming. Therefore, instead of curated annotations most of the proteins come with uncurated annotations, which have been generated automatically. Text-mining systems that use literature for automatic annotation have been proposed but they do not satisfy the high quality expectations of curators. Results: In this paper we describe an approach that links uncurated annotations to text extracted from literature. The selection of the text is based on the similarity of the text to the term from the uncurated annotation. Besides substantiating the uncurated annotations, the extracted texts also lead to novel annotations. In addition, the approach uses the GO hierarchy to achieve high precision. Our approach is integrated into GOAnnotator, a tool that assists the curation process for GO annotation of UniProt proteins. Conclusion: The GO curators assessed GOAnnotator with a set of 66 distinct UniProt/SwissProt proteins with uncurated annotations. GOAnnotator provided correct evidence text at 93% precision. This high precision results from using the GO hierarchy to only select GO terms similar to GO terms from uncurated annotations in GOA. Our approach is the first one to achieve high precision, which is crucial for the efficient support of GO curators. GOAnnotator was implemented as a web tool that is freely available at http://xldb.di.fc.ul.pt/rebil/tools/goa/. http://www.biomedcentral.com/1747-5333/1/19 Francisco Couto Mario Silva Vivian Lee Emily Dimmer Evelyn Camon Rolf Apweiler Harald Kirsch Dietrich Rebholz-Schuhmann Journal of Biomedical Discovery and Collaboration 2006, 1:19 2006-12-20T00:00:00Z doi:10.1186/1747-5333-1-19 Journal of Biomedical Discovery and Collaboration 1747-5333 1 19 2006-12-20T00:00:00Z XML