SEALIFE

How can the researcher in the lab benefit from this new infra-structure to science? A technology is needed to transparently bring such services to the desks of the scientists. Sealife will develop a browser, which will link the existing Web to the currently emerging eScience infrastructure.

Currently, much effort is spent on creating a new computational and data infrastructure to facilitate eScience, the cooperation of geographically distributed organisations, which transparently integrate their computational and data resources at a structural and semantic level. Progress has been made with standards for grid computing and semantic representations for life science data with many projects creating a host of grid-enabled services for the life sciences.

The Web started with a browser and a handful of Web pages. The vision of eScience with an underlying Grid and Semantic Web will only take off with the development of a Semantic Grid browser. The SEALIFE project is filling this gap by developing such a semantic grid browser. These browsers will operate on top of the existing Web, but they introduce an additional semantic level, thus implementing a Semantic Web. Using ontologies as background knowledge, the browsers can automatically identify entities such as protein and gene names, molecular processes, diseases, types of tissue, etc. and the relationships between them, in any Web document. They collect these entities and then apply further analyses to them using applicable Web and Grid services. The SEALIFE browser will be evaluated in three applications relating to the study of infectious diseases.

For further information, please visit:
http://www.biotec.tu-dresden.de/sealife

Project co-ordinator:
TU Dresden

Partners:

  • TU Dresden, (DE)
  • Hariot-Watt University, Edinburgh, (UK)
  • City University, London, (UK)
  • University of Manchester, (UK)
  • Scionics GmbH, Dresden, (DE)
  • Inria, Sophia-Antipolis, (FR)

Timetable: from 4/2006 to 3/2009

Total cost: € 2.6M

EC funding: € 2.2M

Instrument: STREP

Project Identifier: IST-2004-027269

Source: FP6 eHealth Portfolio of Projects

Most Popular Now

Do Fitness Apps do More Harm than Good?

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts may...

AI Tool Beats Humans at Detecting Parasi…

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially transforming how labs diagnose...

Making Cancer Vaccines More Personal

In a new study, University of Arizona researchers created a model for cutaneous squamous cell carcinoma, a type of skin cancer, and identified two mutated tumor proteins, or neoantigens, that...

AI can Better Predict Future Risk for He…

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack. The study, conducted by an international...

A New AI Model Improves the Prediction o…

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the...

AI, Health, and Health Care Today and To…

Artificial intelligence (AI) carries promise and uncertainty for clinicians, patients, and health systems. This JAMA Summit Report presents expert perspectives on the opportunities, risks, and challenges of AI in health...

AI System Finds Crucial Clues for Diagno…

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to interpret quickly...

Improved Cough-Detection Tech can Help w…

Researchers have improved the ability of wearable health devices to accurately detect when a patient is coughing, making it easier to monitor chronic health conditions and predict health risks such...

New AI Tool Makes Medical Imaging Proces…

When doctors analyze a medical scan of an organ or area in the body, each part of the image has to be assigned an anatomical label. If the brain is...