Special Issue "Application of Information Theory in Biomedical Data Mining"
Deadline for manuscript submissions: closed (31 July 2019).
In this era of big data in biomedicine, we now have access to high-throughput, high-dimensional complex data collected to help to better understand the biology of living systems. The availability of more data does not, however, guarantee more knowledge, unless more advanced and powerful data analysis tools are developed to help us to mine the data and extract that knowledge. The high-dimensionality, heterogeneity, and complexity of biomedical big data renders many traditional statistical and computational methods obsolete and thus, the area of biomedical data mining calls for new algorithms and methods that embrace complexity.
Information theory originates from information science and was developed to quantify, store, and transmit information. Information theoretical measures have been used to quantify correlations and interactions of attributes in biomedical data mining and hold great potential.
In this Special Issue, we would like to feature a series of novel applications of information theoretical measures for biomedical data mining. We welcome any original articles relating to, but not limited to, the topics described herein.
Dr. Ting Hu
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- information theory
- mutual information
- information gain
- big data
- data mining