Data Mining for Biomarker Discovery by Stefania Mondello, Firas Kobeissy, Isaac Fingers (auth.),
By Stefania Mondello, Firas Kobeissy, Isaac Fingers (auth.), Panos M. Pardalos, Petros Xanthopoulos, Michalis Zervakis (eds.)
Biomarker discovery is a crucial zone of biomedical study that can result in major breakthroughs in sickness research and specific remedy. Biomarkers are organic entities whose changes are measurable and are attribute of a specific organic . learning, handling, and studying wisdom of latest biomarkers are difficult and engaging difficulties within the rising box of biomedical informatics.
This quantity is a suite of state of the art study into the appliance of knowledge mining to the invention and research of latest biomarkers. providing new effects, types and algorithms, the incorporated contributions concentrate on biomarker information integration, info retrieval equipment, and statistical desktop studying techniques.
This quantity is meant for college students, and researchers in bioinformatics, proteomics, and genomics, to boot engineers and utilized scientists drawn to the interdisciplinary software of knowledge mining techniques.
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We concluded that a global feature subset of 16 most frequent features can play the role of a biomarker and distinguish early and late preictal states. 1 Introduction In data mining problems regarding time series, it is important to find time series features that each captures a different characteristic of the time series and all together represent well the information in the time series. The selection of only A. Tsimpiris • D. M. Pardalos et al. 1007/978-1-4614-2107-8 3, © Springer Science+Business Media, LLC 2012 31 32 A.