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Computational Models for the Analysis of Modern Biological Data

Computational Models for the Analysis of Modern Biological Data
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Author(s): Tuan D. Pham (James Cook University, Australia)
Copyright: 2009
Pages: 9
Source title: Handbook of Research on Systems Biology Applications in Medicine
Source Author(s)/Editor(s): Andriani Daskalaki (Max Planck Institute for Molecular Genetics, Germany)
DOI: 10.4018/978-1-60566-076-9.ch006

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Abstract

Computational models have been playing a significant role for the computer-based analysis of biological and biomedical data. Given the recent availability of genomic sequences and microarray gene expression, and proteomic data, there is an increasing demand for developing and applying advanced computational techniques for exploring these types of data such as: functional interpretation of gene expression data, deciphering of how genes, and proteins work together in pathways and networks, extracting and analysing phenotypic features of mitotic cells for high throughput screening of novel anti-mitotic drugs. Successful applications of advanced computational algorithms to solving modern life-science problems will make significant impacts on several important and promising issues related to genomic medicine, molecular imaging, and the scientific knowledge of the genetic basis of diseases. This chapter reviews the fusion of engineering, computer science, and information sciences with biology and medicine to address some latest technical developments in the computational analyses of modern biological data: microarray gene expression data, mass spectrometry data, and bioimaging.

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