Molidor Robert, Sturn Alexander, Maurer Michael, Trajanoski Zlatko
Institute of Biomedical Engineering and Christian Doppler Laboratory for Genomics and Bioinformatics, Graz University of Technology, Krenngasse 37, Graz, 8010, Austria.
Exp Gerontol. 2003 Oct;38(10):1031-6. doi: 10.1016/s0531-5565(03)00168-2.
Molecular medicine requires the integration and analysis of genomic, molecular, cellular, as well as clinical data and it thus offers a remarkable set of challenges to bioinformatics. Bioinformatics nowadays has an essential role both, in deciphering genomic, transcriptomic, and proteomic data generated by high-throughput experimental technologies, and in organizing information gathered from traditional biology and medicine. The evolution of bioinformatics, which started with sequence analysis and has led to high-throughput whole genome or transcriptome annotation today, is now going to be directed towards recently emerging areas of integrative and translational genomics, and ultimately personalized medicine.Therefore considerable efforts are required to provide the necessary infrastructure for high-performance computing, sophisticated algorithms, advanced data management capabilities, and-most importantly-well trained and educated personnel to design, maintain and use these environments. This review outlines the most promising trends in bioinformatics, which may play a major role in the pursuit of future biological discoveries and medical applications.
分子医学需要整合和分析基因组、分子、细胞以及临床数据,因此给生物信息学带来了一系列重大挑战。如今,生物信息学在解读高通量实验技术生成的基因组、转录组和蛋白质组数据,以及整理从传统生物学和医学收集的信息方面都发挥着至关重要的作用。生物信息学的发展始于序列分析,如今已发展到高通量全基因组或转录组注释,现在正朝着整合和转化基因组学这一新兴领域,最终朝着个性化医学发展。因此,需要付出巨大努力来提供高性能计算所需的基础设施、复杂的算法、先进的数据管理能力,以及最重要的——训练有素且受过良好教育的人员来设计、维护和使用这些环境。本综述概述了生物信息学中最有前景的趋势,这些趋势可能在未来生物学发现和医学应用的探索中发挥重要作用。