- Johns Hopkins University School of Medicine, Neurology, Faculty MemberJohns Hopkins University School of Medicine, Neurosurgery, Faculty MemberJohns Hopkins University School of Medicine, Radiology, Faculty Memberadd
- Robert Stevens, MD, is an Associate Professor at Johns Hopkins University (JHU) School of Medicine with appointments ... moreRobert Stevens, MD, is an Associate Professor at Johns Hopkins University (JHU) School of Medicine with appointments in Anesthesiology Critical Care Medicine, Neurology, Neurosurgery, and Radiology. He received his degree in medicine from the University of Geneva and completed his residency and fellowship at the University of Geneva and Johns Hopkins University. Dr Stevens’ research aims to apply computational approaches to analyse patient-specific biological signatures encountered in trauma, surgery and acute conditions such as stroke, cardiac arrest, and sepsis. To achieve this, he engages with an interdisciplinary group of basic and systems neuroscientists, biomedical and computer engineers, biostatisticians, data scientists, and neuroradiologists. Dr Stevens is the principal investigator of the Neuroimaging for Coma Emergence and Recovery (NICER) project, which examines MRI features of the brain connectome to enhance classification and prediction in patients recovering from severe brain injury. Other projects from Dr Stevens’ group analyze features captured through neurophysiologic monitoring, structural and functional MRI of the brain, serum biomarkers and wearable sensors, with the goal of enhancing classification and prediction in vulnerable, acutel ill patients. In the lab, Dr Stevens’ group studies molecular and cellular determinants of injury and recovery in experimental models of traumatic brain injury, stroke, and sepsis, with a special emphasis on neuro-immunological responses and cellular regeneration.(Robert Stevens, MD, is an Associate Professor at Johns Hopkins University (JHU) School of Medicine with appointments in Anesthesiology Critical Care Medicine, Neurology, Neurosurgery, and Radiology. He received his degree in medicine from the University of Geneva and completed his residency and fellowship at the University of Geneva and Johns Hopkins University. Dr Stevens’ research aims to apply computational approaches to analyse patient-specific biological signatures encountered in trauma, surgery and acute conditions such as stroke, cardiac arrest, and sepsis. To achieve this, he engages with an interdisciplinary group of basic and systems neuroscientists, biomedical and computer engineers, biostatisticians, data scientists, and neuroradiologists. Dr Stevens is the principal investigator of the Neuroimaging for Coma Emergence and Recovery (NICER) project, which examines MRI features of the brain connectome to enhance classification and prediction in patients recovering from severe brain injury. Other projects from Dr Stevens’ group analyze features captured through neurophysiologic monitoring, structural and functional MRI of the brain, serum biomarkers and wearable sensors, with the goal of enhancing classification and prediction in vulnerable, acutel ill patients. In the lab, Dr Stevens’ group studies molecular and cellular determinants of injury and recovery in experimental models of traumatic brain injury, stroke, and sepsis, with a special emphasis on neuro-immunological responses and cellular regeneration.)edit
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The Semantic Web and the Knowledge Grid are recently proposed technological solutions to distributed knowledge management. Early experimental applications from the Life Science community indicate that the approaches have promise and... more
The Semantic Web and the Knowledge Grid are recently proposed technological solutions to distributed knowledge management. Early experimental applications from the Life Science community indicate that the approaches have promise and suggest that this community be an appropriate nursery for grounding, developing and hardening the current, rather immature, machinery needed to deliver on the technological visions, which thus far have been dominated by technological curiosity rather than application-led practicality and relevance. Further necessary developments in theory, infrastructure, tools, and content management should and could be steered opportunistically by the needs and applications of Life Science.:
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Many bioinformatics resources hold data in the form of sequences. Often this sequence data is associated with a large amount of annota- tion. In many cases this data has been hard to model, and has been represented as scientic natural... more
Many bioinformatics resources hold data in the form of sequences. Often this sequence data is associated with a large amount of annota- tion. In many cases this data has been hard to model, and has been represented as scientic natural language, which is not readily compu- tationally amenable. The development of the Gene Ontology provides us with a more accessible
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Text definitions for entities within bio-ontologies are a cornerstone of the effort to gain a consensus in understanding and usage of those ontologies. Writing these definitions is, however, a considerable effort and there is often a lag... more
Text definitions for entities within bio-ontologies are a cornerstone of the effort to gain a consensus in understanding and usage of those ontologies. Writing these definitions is, however, a considerable effort and there is often a lag between specification of the main part of an ontology (logical descriptions and definitions of entities) and the development of the text-based definitions. The goal of natural language generation (NLG) from ontologies is to take the logical description of entities and generate fluent natural language. The application described here uses NLG to automatically provide text-based definitions from an ontology that has logical descriptions of its entities, so avoiding the bottleneck of authoring these definitions by hand. To produce the descriptions, the program collects all the axioms relating to a given entity, groups them according to common structure, realises each group through an English sentence, and assembles the resulting sentences into a paragra...
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The bio-ontology community falls into two camps: first we have biology domain experts, who actually hold the knowledge we wish to capture in ontologies; second, we have ontology specialists, who hold knowledge about techniques and best... more
The bio-ontology community falls into two camps: first we have biology domain experts, who actually hold the knowledge we wish to capture in ontologies; second, we have ontology specialists, who hold knowledge about techniques and best practice on ontology development. In the bio-ontology domain, these two camps have often come into conflict, especially where pragmatism comes into conflict with perceived best practice. One of these areas is the insistence of computer scientists on a well-defined semantic basis for the Knowledge Representation language being used. In this article, we will first describe why this community is so insistent. Second, we will illustrate this by examining the semantics of the Web Ontology Language and the semantics placed on the Directed Acyclic Graph as used by the Gene Ontology. Finally we will reconcile the two representations, including the broader Open Biomedical Ontologies format. The ability to exchange between the two representations means that we ...
Research Interests: Programming Languages, Artificial Intelligence, Natural Language Processing, Computational Biology, Ontology Development, and 13 moreKnowledge Representation, Database Management Systems, Biological Sciences, Phylogeny, Mathematical Sciences, Best practice, Gene ontology, BMC Bioinformatics, Proteins, Genes, Computer User Interface Design, Information Storage and Retrieval, and Directed Acyclic Graph
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Abstract. Biological knowledge has been, to date, coded by biologists in axiomatically lean bio-ontologies. To facilitate axiomatic enrichment, complex semantics can be encapsulated as Ontology Design Patterns (ODPs). These can be applied... more
Abstract. Biological knowledge has been, to date, coded by biologists in axiomatically lean bio-ontologies. To facilitate axiomatic enrichment, complex semantics can be encapsulated as Ontology Design Patterns (ODPs). These can be applied across an ontology to make the ...
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The paper documents a series of data integration workshops held in 2006 at the UK National e-Science Centre, summarizing a range of the problem/solution scenarios in multi-site and multi-scale data integration with six HealthGrid projects... more
The paper documents a series of data integration workshops held in 2006 at the UK National e-Science Centre, summarizing a range of the problem/solution scenarios in multi-site and multi-scale data integration with six HealthGrid projects using schizophrenia as a domain-specific test case. It outlines emerging strategies, recommendations and objectives for collaboration on shared ontology-building and harmonization of data for multi-site trials in this domain.
Research Interests: Education, Medical Informatics, Health Studies, Systems Integration, Library and Information Studies, and 11 moreHumans, Medical Oncology, eHealth, Great Britain, Data Integrity, Phycics, Ontology Integration, Public health systems and services research, Sociotechnical, eInfrastructure, and HealthGrid
It is well known that many Web pages are difficult for visually disabled people to use. Without access to a rich, visual display, the intended structure and organisation of the page is obscured. To fully understand what is missing from... more
It is well known that many Web pages are difficult for visually disabled people to use. Without access to a rich, visual display, the intended structure and organisation of the page is obscured. To fully understand what is missing from the experience of visually disabled users, it is pertinent to ask how the presentation of Web pages on a standard
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Surface sediments were sampled with an Oktopus box corer at 29 stations, during the cruise Paleo1, in 3 areas of the Portuguese continental shelf located at the mouth of 4 rivers (Ave, Douro, Lis and Mira). These shelf areas were chosen... more
Surface sediments were sampled with an Oktopus box corer at 29 stations, during the cruise Paleo1, in 3 areas of the Portuguese continental shelf located at the mouth of 4 rivers (Ave, Douro, Lis and Mira). These shelf areas were chosen show different levels of urban and industrial impact, as well as different geological and climate settings. The main goal
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Abstract: Life Science research has extended beyond in vivo and in vitro bench-bound science to incorporate in silico knowledge discovery, using resources that have been developed over time by different teams for different purposes and in... more
Abstract: Life Science research has extended beyond in vivo and in vitro bench-bound science to incorporate in silico knowledge discovery, using resources that have been developed over time by different teams for different purposes and in different forms. The myGrid project has developed a set of software components and a workbench, Taverna, for building, running and sharing workflows that link third party bioinformatics services, such as databases, analytic tools and applications. Intelligently discovering prior services, ...