Title |
A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience
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Published in |
BMC Medical Informatics and Decision Making, October 2012
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DOI | 10.1186/1472-6947-12-115 |
Pubmed ID | |
Authors |
Luca Corradi, Ivan Porro, Andrea Schenone, Parastoo Momeni, Raffaele Ferrari, Flavio Nobili, Michela Ferrara, Gabriele Arnulfo, Marco M Fato |
Abstract |
Robust, extensible and distributed databases integrating clinical, imaging and molecular data represent a substantial challenge for modern neuroscience. It is even more difficult to provide extensible software environments able to effectively target the rapidly changing data requirements and structures of research experiments. There is an increasing request from the neuroscience community for software tools addressing technical challenges about: (i) supporting researchers in the medical field to carry out data analysis using integrated bioinformatics services and tools; (ii) handling multimodal/multiscale data and metadata, enabling the injection of several different data types according to structured schemas; (iii) providing high extensibility, in order to address different requirements deriving from a large variety of applications simply through a user runtime configuration. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 2 | 50% |
United States | 1 | 25% |
Unknown | 1 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 3 | 75% |
Members of the public | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 2% |
Italy | 1 | 2% |
Unknown | 60 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 13 | 21% |
Student > Ph. D. Student | 7 | 11% |
Librarian | 5 | 8% |
Student > Master | 5 | 8% |
Student > Bachelor | 4 | 6% |
Other | 14 | 23% |
Unknown | 14 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 14 | 23% |
Medicine and Dentistry | 8 | 13% |
Engineering | 5 | 8% |
Agricultural and Biological Sciences | 4 | 6% |
Arts and Humanities | 3 | 5% |
Other | 12 | 19% |
Unknown | 16 | 26% |