Background: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature.

Developing cures for highly complex diseases, such as neurodegenerative disorders, requires extensive interdisciplinary collaboration and exchange of biomedical information in context. Our ability to exchange such information across sub-specialties today is limited by the current scientific knowledge ecosystem's inability to properly contextualize and integrate data and discourse in machine-interpretable form. This inherently limits the productivity of research and the progress toward cures for devastating diseases such as Alzheimer's and Parkinson's. SWAN (Semantic Web Applications in Neuromedicine) is an interdisciplinary project to develop a practical, common, semantically structured, framework for biomedical discourse initially applied, but not limited, to significant problems in Alzheimer Disease (AD) research. The SWAN ontology has been developed in the context of building a series of applications for biomedical researchers, as well as in extensive discussions and collaborations with the larger bio-ontologies community. In this paper, we present and discuss the SWAN ontology of biomedical discourse. We ground its development theoretically, present its design approach, explain its main classes and their application, and show its relationship to other ongoing activities in biomedicine and bio-ontologies.

Scientists drove the early development of the World Wide Web, primarily as a means for rapid communication, document sharing and data access. They have been far slower to adopt the web as a medium for building research communities. Yet, web-based communities hold great potential for accelerating the pace of scientific research. In this article, we will describe the 10-year experience of the Alzheimer Research Forum ('Alzforum'), a unique example of a thriving scientific web community, and explain the features that contributed to its success. We will then outline the SWAN (Semantic Web Applications in Neuromedicine) project, in which Alzforum curators are collaborating with informatics researchers to develop novel approaches that will enable communities to share richly contextualized information about scientific data, claims and hypotheses.

The Alzheimer Research Forum Web site ( http://www.alzforum.org ) is an independent research project to develop an online community resource to manage scientific knowledge, information, and data about Alzheimer disease (AD). Its goals are to promote rapid communication, research efficiency, and collaborative, multidisciplinary interactions. Introducing new knowledge management approaches to AD research has a potentially large societal value. AD is among the leading causes of disability and death in older people. According to the Alzheimer's Association, four million Americans currently suffer from AD. That number is expected to escalate to over 10 million in coming decades. Patients progress from memory loss to a bedridden state over many years and require near-constant care. In addition to imposing a heavy burden on family caregivers and society at large, AD and related neurodegenerative disorders are among the most complex and challenging in biomedicine. Researchers have produced an abundance of data implicating diverse biological mechanisms. Important factors include genes, environmental risks, changes in cell functions, DNA damage, accumulation of misfolded proteins, cell death, immune responses, changes related to aging, and reduced regenerative capacity. Yet there is no agreement on the fundamental causes of AD. The situations regarding Parkinson, Huntington, and amyotrophic lateral sclerosis (ALS) are similar. The challenge of integrating so much data into testable hypotheses and unified concepts is formidable. What is more, basic understanding of these diseases needs to intersect with an equally complex universe of pharmacology, medicinal chemistry, animal studies, and clinical trials. In this chapter, we will describe the approaches developed by Alzforum to achieve knowledge integration through information technology and virtual community-building. We will also propose some future directions in the application of Web-based knowledge management systems in neuromedicine.

Background: Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, eNeuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data.

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Facioscapulohumeral muscular dystrophy (FSHD) is the second most common genetic myopathy, characterized by slowly progressing and highly heterogeneous muscle wasting with a typical onset in the late teens/early adulthood [1]. Although the etiology of the disease for both FSHD type 1 and type 2 has been attributed to gain-of-toxic function stemming from aberrant DUX4 expression, the exact pathogenic mechanisms involved in muscle wasting have yet to be elucidated [2–4]. The 2021 FSHD International Research Congress, held virtually on June 24–25, convened over 350 researchers and clinicians to share the most recent advances in the understanding of the disease mechanism, discuss the proliferation of interventional strategies and refinement of clinical outcome measures, including results from the ReDUX4 trial, a phase 2b clinical trial of losmapimod in FSHD [NCT04003974].

Alzheimer disease (AD) is a neurodegenerative condition leading to progressive, irreversible loss of cognitive and behavioral function. Despite considerable investments in neuroscience research, only four drugs, all cholinesterase inhibitors, have been approved for the symptomatic management of AD in the United States. Although basically safe and modestly effective, these drugs are far from ideal, being neither universally efficacious nor disease modifying. AD exacts a considerable toll in direct medical costs, quality of life, and caregiver burden for persons and society. In addition to the obvious clinical benefit, therapeutic agents for AD and related dementias represent a considerable market opportunity for the pharmaceutical and biotechnology industries. There are currently 8-10 million AD sufferers in the seven major pharmaceutical markets. The market will grow rapidly in coming decades, as the developed world experiences an enormous increase in its elderly population. Given the great need for new therapeutic agents to manage and prevent AD, the Institute for the Study of Aging and the Fidelity Foundation organized a workshop, "Barriers to the Discovery and Development of Drugs for Alzheimer's Disease," to examine ways to expedite drug discovery and development. The identified barriers and potential solutions will be discussed here and in the accompanying articles in more detail.