التفاصيل البيبلوغرافية
| العنوان: |
Database application model and its service for drug discovery in Model-driven architecture |
| المؤلفون: |
Etani, Noriko |
| المساهمون: |
江谷, 典子 |
| بيانات النشر: |
SpringerOpen |
| سنة النشر: |
2015 |
| المجموعة: |
Kyoto University Research Information Repository (KURENAI) / 京都大学学術情報リポジトリ |
| مصطلحات موضوعية: |
PLS regression analysis, Discriminant analysis, Support vector machine, Prediction model, Drug side effect, Drug discovery, Model-driven architecture (MDA) |
| الوصف: |
Big data application has many data resources and data. In the first stage of software engineering, a service overview or a system overview cannot be seen. In this paper, we propose that two processes of “Big data analytics” and “Implementation of data modeling” should be collaborated with Model-driven architecture (MDA). Data modeling with those two process in MDA should be repeated fast in order to verify the data model and to find a new data resource for a service. Our first research goal of big data application is to predict side effect of drug which is one of screening methods in drug discovery. This prediction model is constructed with data mining methods at the intersection of statistics, machine learning and database system. Moreover, a new service for drug discovery by new uses for old drugs can be found in data modeling and developed. We demonstrate that the prediction model and the data model for drug discovery are implemented as a prototype system to verify those models and their practicality. |
| نوع الوثيقة: |
article in journal/newspaper |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| تدمد: |
2196-1115 |
| العلاقة: |
http://hdl.handle.net/2433/203164Test; Journal of Big Data; 16 |
| الإتاحة: |
http://hdl.handle.net/2433/203164Test |
| حقوق: |
© 2015 Etani. ; This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0Test), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0Test/) applies to the data made available in this article, unless otherwise stated. |
| رقم الانضمام: |
edsbas.C44889F3 |
| قاعدة البيانات: |
BASE |
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