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首页> 外文期刊>The Open Dentistry Journal >Bioinformatics and Data Mining Studies in Oral Genomics and Proteomics: New Trends and Challenges
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Bioinformatics and Data Mining Studies in Oral Genomics and Proteomics: New Trends and Challenges

机译:口腔基因组学和蛋白质组学中的生物信息学和数据挖掘研究:新趋势和新挑战

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Genomics and proteomics have promised to change the practice of dentistry and oral pathology, allowing the identification and the characterization of risk factors and therapeutic targets at a molecular level. However, mass-scale molecular genomics and proteomics suffer from some pitfalls: gene/protein expression are significant only if inserted in a detailed network of molecular pathways and gene/gene, gene/protein and protein/protein interactions. The proper analysis of these complex pictures requires the contribution of theoretical disciplines, like bioinformatics and data mining. In particular, data-mining of existing information could become a strong starting point to formulate new targeted hypotheses and to plan ad hoc experimentation.In this review, advantages and disadvantages of the above-mentioned disciplines and their potential in oral pathology are discussed. The leader gene approach is a new data mining algorithm, recently applied to some oral diseases and their correlation with systemic conditions. The preliminary results of the application of the leader gene approach to the correlation between periodontitis and heart ischemia at a molecular level are presented for the first time.
机译:基因组学和蛋白质组学已有望改变牙科和口腔病理学的实践,从而可以在分子水平上鉴定和表征危险因素和治疗靶标。但是,大规模的分子基因组学和蛋白质组学存在一些陷阱:仅当插入分子途径和基因/基因,基因/蛋白质以及蛋白质/蛋白质相互作用的详细网络中时,基因/蛋白质的表达才有意义。对这些复杂图片的正确分析需要理论学科的贡献,例如生物信息学和数据挖掘。特别是,现有信息的数据挖掘可能成为制定新的针对性假设和计划临时实验的强大起点。在本综述中,将讨论上述学科的优缺点及其在口腔病理学中的潜力。前导基因方法是一种新的数据挖掘算法,最近已应用于某些口腔疾病及其与全身疾病的相关性。首次介绍了在分子水平上应用前导基因方法在牙周炎和心脏缺血之间相关性的初步结果。

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