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Data Mining Strategies Applied in Brain Injury Models

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Data Mining for Biomarker Discovery

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 65))

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Abstract

Traumatic brain injury or traumatic head injury is characterized as a direct physical impact or trauma to the head, causing brain injury. It represents a major national health problem without a US Food and Drug Administration-approved therapy. The application of neuroproteomics/neurogenomics has revolutionized the characterization of protein/gene dynamics, leading to a greater understanding of post-injury biochemistry. Neuroproteomics and Neurogenomics fields have undertaken major advances in the area of neurotrauma research focusing on biomarker identification. Several candidate markers have been identified and are being evaluated for their efficacy as biological biomarkers utilizing these “omics approaches”. The identification of these differentially expressed candidate markers using these techniques is proving to be only the first step in the biomarker development process. However, to translate these findings into the clinic, data-driven development cycle incorporating data-mining steps for discovery, qualification, verification, and clinical validation is needed. Data mining steps extend beyond the collected data level into an integrated scheme of animal modeling, instrumentation, and functional data analysis. In this chapter, we provide an introductory review of data-mining/systems biology coupled approaches that have been applied to biomarker discovery and clinical validation; in addition, the need for strengthening the integral roles of these disciplines in establishing a comprehensive understanding of specific brain disorder and biomarker identification in general.

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Author information

Authors and Affiliations

  1. Banyan Biomarkers, Alachua, FL, 32615, USA

    Stefania Mondello, Firas Kobeissy, Isaac Fingers, Zhiqun Zhang, Ronald L. Hayes & Kevin K. W. Wang

Authors
  1. Stefania Mondello
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  2. Firas Kobeissy
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  3. Isaac Fingers
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  4. Zhiqun Zhang
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  5. Ronald L. Hayes
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  6. Kevin K. W. Wang
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Corresponding author

Correspondence to Stefania Mondello .

Editor information

Editors and Affiliations

  1. , Department of Industrial & Systems Engin, University of Florida, Weil Hall 401, Gainesville, 32611-6595, Florida, USA

    Panos M. Pardalos

  2. , Department of Industrial & Systems Engin, University of Florida, Weil Hall 401, Gainesville, 32611, Florida, USA

    Petros Xanthopoulos

  3. Dept. Electronic & Computer, Engineering, Technical University of Crete, Chania, Crete, 731 00, Greece

    Michalis Zervakis

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Mondello, S., Kobeissy, F., Fingers, I., Zhang, Z., Hayes, R.L., Wang, K.K.W. (2012). Data Mining Strategies Applied in Brain Injury Models. In: Pardalos, P., Xanthopoulos, P., Zervakis, M. (eds) Data Mining for Biomarker Discovery. Springer Optimization and Its Applications(), vol 65. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-2107-8_1

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