Anatomy of cluster development in China: The case of health biotech clusters

Focussing on China's health biotech clusters the study explores the anatomy of interaction in as well as between various clusters. While the literature has identified the existence of a dense network of durable interactions among firms and between firms and academia at a particular location as one of the most important prerequisites for well-performing clusters, we show that network ties extending beyond regional boundaries are equally valuable for the innovative capacity of China's biotech firms. Analysing the demographic process of cluster emergence we show that there exist different types of biotech clusters in China, which are closely linked and exchange knowledge and technology amongst each other. It appears as if further analysis of these cross-cluster links may provide important insights of how learning and innovation works in China's health biotech industry. Although China's science parks and industrial bases may on an individual basis appear to be badly structured, the organization of China's health biotech industry turns out to be substantially enhanced once these external linkages are taken into consideration. --China,health biotechnology,cluster,entrepreneurship,localization

OHMI: The Ontology of Host-Microbiome Interactions

Host-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases, and extensive HMI studies have generated large amounts of data. We propose that the logical representation of the knowledge derived from these data and the standardized representation of experimental variables and processes can foster integration of data and reproducibility of experiments and thereby further HMI knowledge discovery. A community-based Ontology of Host-Microbiome Interactions (OHMI) was developed following the OBO Foundry principles. OHMI leverages established ontologies to create logically structured representations of microbiomes, microbial taxonomy, host species, host anatomical entities, and HMIs under different conditions and associated study protocols and types of data analysis and experimental results

Infectious Disease Ontology

Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain

1st INCF Workshop on Sustainability of Neuroscience Databases

The goal of the workshop was to discuss issues related to the sustainability of neuroscience databases, identify problems and propose solutions, and formulate recommendations to the INCF. The report summarizes the discussions of invited participants from the neuroinformatics community as well as from other disciplines where sustainability issues have already been approached. The recommendations for the INCF involve rating, ranking, and supporting database sustainability

The physiologic correlates of learning in the classroom environment

This study served to further investigate learning and memory, and to offer a potential tool to support educational interventions. More specifically, this was accomplished by an investigation of the physiologic changes in the brain that occurred while students learned medical anatomy. A group of 29 students taking the Gross Anatomy course at Boston University School of Medicine participated in the study. Testing occurred in two sessions: prior to the course and at the completion of the course. For each session, scalp EEG was recorded while participants were shown 176 anatomical terms (132 relevant to the course and 44 obscure) and asked to respond with "Can Define", "Familiar", or "Don't Know". Behavioral results indicated a positive correlation between participants' course grades and performance on the experimental tasks. EEG results were analyzed for event-related potential (ERP) components related to two memory components: familiarity and recollection. Results had a number of indications. For Don't Know responses, a stronger early frontal, late parietal, and late frontal effect occurred more so for terms of Session 1 compared to Session 2. For an analysis of just Session 2 data, results indicated increased activity of the early frontal, late parietal, and late frontal effects for Can Define responses only. Session 2 Can Define responses elicited a stronger early frontal ERP, occurring between 300 and 500 milliseconds yet, the most post-retrieval processing and monitoring appeared for Can Define terms of Session 2. Ultimately, we focused on investigating two points: 1) the effect of classroom learning on memory, and 2) the examination of ERPs as a tool to guide education interventions. Specifically, ERPs would potentially indicate markers to predict whether students would retain materials long before behavioral measures indicate these results. This has potential to determine whether long-lasting or transient learning will occur; as well as the potential to support early intervention strategies for not just students, but also individuals with learning disabilities or memory impairments

Technology and the economy

Overview of economics of innovatio

Applications and Uses of Dental Ontologies

The development of a number of large-scale semantically-rich ontologies for biomedicine attests to the interest of life science researchers and clinicians in Semantic Web technologies. To date, however, the dental profession has lagged behind other areas of biomedicine in developing a commonly accepted, standardized ontology to support the representation of dental knowledge and information. This paper attempts to identify some of the potential uses of dental ontologies as part of an effort to motivate the development of ontologies for the dental domain. The identified uses of dental ontologies include support for advanced data analysis and knowledge discovery capabilities, the implementation of novel education and training technologies, the development of information exchange and interoperability solutions, the better integration of scientific and clinical evidence into clinical decision-making, and the development of better clinical decision support systems. Some of the social issues raised by these uses include the ethics of using patient data without consent, the role played by ontologies in enforcing compliance with regulatory criteria and legislative constraints, and the extent to which the advent of the Semantic Web introduces new training requirements for dental students. Some of the technological issues relate to the need to extract information from a variety of resources (for example, natural language texts), the need to automatically annotate information resources with ontology elements, and the need to establish mappings between a variety of existing dental terminologies

Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies

A systematic search of the research literature from 1996 through July 2008 identified more than a thousand empirical studies of online learning. Analysts screened these studies to find those that (a) contrasted an online to a face-to-face condition, (b) measured student learning outcomes, (c) used a rigorous research design, and (d) provided adequate information to calculate an effect size. As a result of this screening, 51 independent effects were identified that could be subjected to meta-analysis. The meta-analysis found that, on average, students in online learning conditions performed better than those receiving face-to-face instruction. The difference between student outcomes for online and face-to-face classes—measured as the difference between treatment and control means, divided by the pooled standard deviation—was larger in those studies contrasting conditions that blended elements of online and face-to-face instruction with conditions taught entirely face-to-face. Analysts noted that these blended conditions often included additional learning time and instructional elements not received by students in control conditions. This finding suggests that the positive effects associated with blended learning should not be attributed to the media, per se. An unexpected finding was the small number of rigorous published studies contrasting online and face-to-face learning conditions for K–12 students. In light of this small corpus, caution is required in generalizing to the K–12 population because the results are derived for the most part from studies in other settings (e.g., medical training, higher education)