Web-services-based resource discovery model and service deployment on HealthGrids.

IEEE Trans Inf Technol Biomed

School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, UK.

Published: May 2010

HealthGrids represent the next generation of advanced healthcare IT and hold the promise to untangle complex healthcare-data problems by integrating health information systems and healthcare entities. Healthcare could benefit from a new delivery approach using HealthGrids to better meet the biomedical and health-related needs. Specialized services are needed to provide unified discovery of and ubiquitous access to available HealthGrid resources. The different types of services available on HealthGrids are classified into two levels, the operational-level services and the management-level services. This paper takes a fresh approach to address the problems of resource discovery in HealthGrids based on Web services (WS) and WS technologies and proposes a WS-based resource discovery model.

Download full-text PDF

Source
http://dx.doi.org/10.1109/TITB.2010.2040482DOI Listing

Publication Analysis

Top Keywords

resource discovery
12
discovery model
8
healthgrids
5
services
5
web-services-based resource
4
discovery
4
model service
4
service deployment
4
deployment healthgrids
4
healthgrids healthgrids
4

Similar Publications

To optimize the utilization of the sea star , which has demonstrated potential pharmaceutical properties in Chinese folk medicine, ten glycosides of polyhydroxy steroids, pectiniferosides A-J (-), were isolated and characterized. These compounds possess 3β, 6α, 8, 15α (or β), 16β-pentahydroxycholestane aglycones with sulfated and (or) methylated monosaccharides. The chemical structures of - were determined using NMR spectroscopy and HR-ESI-MS.

View Article and Find Full Text PDF

Marine natural products are increasingly utilized in nutrition, cosmetics, and medicine, garnering significant attention from researchers globally. With the expansion of marine resource exploration in recent years, the demand for marine natural products has risen, necessitating rapid and cost-effective activity evaluations using model organisms. Zebrafish, a valuable vertebrate model, has become an efficient tool for screening and identifying safe, active molecules from marine natural products.

View Article and Find Full Text PDF

Editorial: Crop abiotic stress: advances in germplasm/gene discovery and utilization.

Front Plant Sci

December 2024

Shandong Engineering Research Center of Rose Breeding Technology and Germplasm Innovation, School of Life Sciences, Qilu Normal University, Jinan, China.

View Article and Find Full Text PDF

Third generation sequencing transforming plant genome research: Current trends and challenges.

Gene

December 2024

Department of Molecular Biology and Biotechnology, Cotton University, Panbazar, Guwahati, Assam 781001, India. Electronic address:

In recent years, third-generation sequencing (TGS) technologies have transformed genomics and transcriptomics research, providing novel opportunities for significant discoveries. The long-read sequencing platforms, with their unique advantages over next-generation sequencing (NGS), including a definitive protocol, reduced operational time, and real-time sequencing, possess the potential to transform plant genomics. TGS optimizes and enhances the efficiency of data analysis by removing the necessity for time-consuming assembly tools.

View Article and Find Full Text PDF

ConoDL: a deep learning framework for rapid generation and prediction of conotoxins.

J Comput Aided Mol Des

December 2024

Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China.

Conotoxins, being small disulfide-rich and bioactive peptides, manifest notable pharmacological potential and find extensive applications. However, the exploration of conotoxins' vast molecular space using traditional methods is severely limited, necessitating the urgent need of developing novel approaches. Recently, deep learning (DL)-based methods have advanced to the molecular generation of proteins and peptides.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!