Role of Bioinformatics in Nanotechnology: An Initiation towards Personalized Medicine

Role of Bioinformatics in Nanotechnology: An Initiation towards Personalized Medicine

Harishchander Anandaram (Sathyabama University, India)
DOI: 10.4018/978-1-7998-1204-3.ch094

Abstract

Recent advancements in bio-computing and nano-technology accelerated the discovery of novel biomarkers in the emerging field of personalized medicine. Personalized medicine deals with disease detection and therapy from the molecular profile of each individual. Personalized medicine is also called as predictive medicine that uses genetic/molecular information to predict disease development, progression, and clinical outcome. In this chapter, we discuss the advantages of using nanotechnology to understand biological systems with an example of the biomarker discovery of cancer. Recent developments in bio computing served as the base for the identification of multiplexed probes in a nano particle. Together we have correlated the bio molecular signatures with clinical outcomes and we have also addressed an emerging field called bio-nano-informatics to suggest an individual therapy for cancer and other diseases.
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Biomarkers And Their Applications

Bio molecular markers can be an altered or mutant gene, RNA, proteins, lipids, carbohydrates and small metabolites, which can be correlated with a biological behavior and its clinical outcome (Wang et al. 2007; Liotta et al. 2000). Most of the biomarkers are discovered on the basis of molecular profiling studies of association or correlation between a molecular signature and disease behavior. Initially, a study was conducted by Gloub et al. for classifying tumors on the basis of patterns in gene expression had reported. This study had provided a novel insight into tumor pathology by analyzing the stage and grade of tumor along with the understanding of clinical course and response to treatment (Petricoin et al., 2002; Negm et al., 2002; Ludwig & Weistein, 2005; Golub et al., 1999; Ross et al., 2000). Gene expression studies illustrate the fact that “Molecular signatures of each tumor are inflammatory factors of the original lesion with heterogeneity” (Alizadeh et al., 2000).

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