Special Issue on: "Data Mining in Biomedicine"
Guest Editors: Dr. Juan R. Rabuñal, Dr. Julián Dorado, Dr. Alejandro Pazos, University of A Coruña, Spain
Data mining can be defined as the set of computational techniques that, given a complex problem, allow the transformation of the original data into information which can be easily assimilated. For this purpose, a series of techniques can be applied, such as data transformation (calculus), classification (contextualisation or categorisation), cluster analysis (categorisation), anomaly detection (correction), etc. These techniques allow understanding the data more easily (condensing or summarising the data).
One of the fields in which data mining is mostly being applied is biomedicine. Since the sequencing of the human genome in 2001, a large amount of data has been generated, this amount being increased every day. The improvements made in the existing technology (such as genome-wide association studies (GWAS), microarrays, mass spectrometry, etc.) generate a large amount of data from different organisms at different levels, starting from genomic or proteomic levels to epidemiological levels. The analysis of this data requires a change of paradigm. Thus, new computational data mining techniques are essential to analyse at a full extent all of these new information sources.
In this special issue, efforts in data mining in the biomedical field will be published as an attempt to approach this field from different perspectives. Thus, the papers contained in this special issue will be a representation of the latest data mining techniques or of the application of previously existing techniques to this field.
We welcome theoretical, empirical papers, and interesting case studies that are within the scope of this issue. The issue will contain invited papers and papers submitted directly as per instruction below. If the number of accepted papers is more than the need of the special issue, they could appear in a regular IJDMMM issue.
Topics of interest include, but are not limited to:
- Intelligent information systems
- Knowledge representation, visualization and integration
- Knowledge discovery and data mining
- Association studies
- Image analysis
Notes for Prospective Authors
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere.
All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page
Submission due date of full paper: 2 May, 2011
Feedback from referees: 1 June, 2011
Submission due date of revised paper: 4 July, 2011
Notification of acceptance: 15 July, 2011
Submission of final revised paper: 30 July, 2011
Editors and Notes
Prospective authors are welcome to submit an abstract to the guest editors for preliminary feedback on the appropriateness of their planned manuscript. You may send one copy of the full manuscript in the form of an MS Word or PDF file attached to an e-mail (details in Author Guidelines) to the following:
Dr. Juan R. Rabuñal
University of A Coruña
Facultad de Informática
Campus de Elviña S/N
15071. A Coruña
Please include in your submission the title of the Special Issue, the title of the Journal and the name of the Guest Editor