Bioinformatic Primer for Clinical and Translational Science
Bioinformatic Primer for Clinical and Translational Science
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DOI：
10.1111/j.1752-8062.2008.00038.x
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发表时间：
2008-09-01
影响因子：
3.9
通讯作者：
Terzic, Andre
中科院分区：
文献类型：
--
作者：
Faustino, Randolph S.;Chiriac, Anca;Terzic, Andre
高通量技术的出现加速了基因组、转录组和蛋白质组数据的生成和扩展。获取高维数据集需要能够提高存储和检索效率的档案系统，因此已经启动并维护了多个电子储存库以满足这一需求。生物信息学已经从这些错综复杂的动态更新的信息和管理这些信息的工具中进化出来，成为驾驭和破译海量数据固有复杂性的必要手段。大数据集与不同程度的随机噪声相关联，随机噪声有助于有序、多稳定状态与响应刺激而进化的能力之间的平衡，从而显示出生物临界性的一个显著特征。在这种背景下，网络理论已经成为绘制关系图的宝贵工具，这些关系整合了在特定组学类别内共同指导全球功能的离散元素，确实，优先关注基因组、转录或蛋白质组层的功能整体而不是单个分子是系统生物学分析的主要原则。这一新的生物学观点允许检查和预测疾病状况，不仅限于单基因挑战，而且作为共同作用的个性化分子排列的组合来影响表型结果。因此，生物层内和生物层之间的多维数据的生物信息集成具有识别独特生物特征的潜力，为临床和翻译科学的进步提供了一个有利的平台。
The advent of high-throughput technologies has accelerated generation and expansion of genomic, transcriptomic, and proteomic data. Acquisition of high-dimensional datasets requires archival systems that permit efficiency of storage and retrieval, and so, multiple electronic repositories have been initiated and maintained to meet this demand. Bioinformatic science has evolved, from these intricate bodies of dynamically updated information and the tools to manage them, as a necessity to harness and decipher the inherent complexity of high-volume data. Large datasets are associated with a variable degree of stochastic noise that contributes to the balance of an ordered, multistable state with the capacity to evolve in response to stimulus, thus exhibiting a hallmark feature of biological criticality. In this context, the network theory has become an invaluable tool to map relationships that integrate discrete elements that collectively direct global function within a particular-omic category, and indeed, the prioritized focus on the functional whole of the genomic, transcriptomic, or proteomic strata over single molecules is a primary tenet of systems biology analyses. This new biology perspective allows inspection and prediction of disease conditions, not limited to a monogenic challenge, but as a combination of individualized molecular permutations acting in concert to effect a phenotypic outcome. Bioinformatic integration of multidimensional data within and between biological layers thus harbors the potential to identify unique biological signatures, providing an enabling platform for advances in clinical and translational science.