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KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain
BACKGROUND: Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge chall...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691758/ https://www.ncbi.nlm.nih.gov/pubmed/23763826 http://dx.doi.org/10.1186/1471-2105-14-191 |
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author | Holzinger, Andreas Zupan, Mario |
author_facet | Holzinger, Andreas Zupan, Mario |
author_sort | Holzinger, Andreas |
collection | PubMed |
description | BACKGROUND: Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. RESULTS: A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. CONCLUSIONS: The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework. |
format | Online Article Text |
id | pubmed-3691758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36917582013-06-26 KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain Holzinger, Andreas Zupan, Mario BMC Bioinformatics Software BACKGROUND: Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. RESULTS: A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. CONCLUSIONS: The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework. BioMed Central 2013-06-13 /pmc/articles/PMC3691758/ /pubmed/23763826 http://dx.doi.org/10.1186/1471-2105-14-191 Text en Copyright © 2013 Holzinger and Zupan; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Holzinger, Andreas Zupan, Mario KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain |
title | KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain |
title_full | KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain |
title_fullStr | KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain |
title_full_unstemmed | KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain |
title_short | KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain |
title_sort | knodwat: a scientific framework application for testing knowledge discovery methods for the biomedical domain |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691758/ https://www.ncbi.nlm.nih.gov/pubmed/23763826 http://dx.doi.org/10.1186/1471-2105-14-191 |
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