Lisacek F, Chichester C, Gonnet P, Jaillet O, Kappus S, Nikitin F, Roland P, Rossier G, Truong L, Appel R
R&D GeneBio, 25 Avenue de Champel, Geneva 1206, Switzerland.
Comp Funct Genomics. 2004;5(2):190-5. doi: 10.1002/cfg.379.
The central dogma of molecular biology has provided a meaningful principle for data integration in the field of genomics. In this context, integration reflects the known transitions from a chromosome to a protein sequence: transcription, intron splicing, exon assembly and translation. There is no such clear principle for integrating proteomics data, since the laws governing protein folding and interactivity are not quite understood. In our effort to bring together independent pieces of information relative to proteins in a biologically meaningful way, we assess the bias of bioinformatics resources and consequent approximations in the framework of small-scale studies. We analyse proteomics data while following both a data-driven (focus on proteins smaller than 10 kDa) and a hypothesis-driven (focus on whole bacterial proteomes) approach. These applications are potentially the source of specialized complements to classical biological ontologies.
分子生物学的中心法则为基因组学领域的数据整合提供了一个有意义的原则。在这种情况下,整合反映了从染色体到蛋白质序列的已知转变:转录、内含子剪接、外显子组装和翻译。由于蛋白质折叠和相互作用的规律尚未完全理解,因此在整合蛋白质组学数据方面没有这样明确的原则。在我们以生物学上有意义的方式汇集与蛋白质相关的独立信息的过程中,我们在小规模研究的框架内评估生物信息学资源的偏差以及由此产生的近似值。我们在遵循数据驱动(关注小于10 kDa的蛋白质)和假设驱动(关注整个细菌蛋白质组)方法的同时分析蛋白质组学数据。这些应用可能是对经典生物学本体进行专门补充的来源。