Institute for Genomics and Bioinformatics, Graz University of Technology, Graz, Austria.
BMC Genomics. 2010 Feb 10;11 Suppl 1(Suppl 1):S7. doi: 10.1186/1471-2164-11-S1-S7.
Cancer progression is a complex process involving host-tumor interactions by multiple molecular and cellular factors of the tumor microenvironment. Tumor cells that challenge immune activity may be vulnerable to immune destruction. To address this question we have directed major efforts towards data integration and developed and installed a database for cancer immunology with more than 1700 patients and associated clinical data and biomolecular data. Mining of the database revealed novel insights into the molecular mechanisms of tumor-immune cell interaction. In this paper we present the computational tools used to analyze integrated clinical and biomolecular data. Specifically, we describe a database for heterogeneous data types, the interfacing bioinformatics and statistical tools including clustering methods, survival analysis, as well as visualization methods. Additionally, we discuss generic issues relevant to the integration of clinical and biomolecular data, as well as recent developments in integrative data analyses including biomolecular network reconstruction and mathematical modeling.
癌症的进展是一个复杂的过程，涉及肿瘤微环境中多种分子和细胞因素的宿主-肿瘤相互作用。挑战免疫活性的肿瘤细胞可能容易受到免疫破坏。为了解决这个问题，我们将主要精力集中在数据集成上，并开发和安装了一个包含 1700 多名患者及相关临床和生物分子数据的癌症免疫学数据库。对该数据库的挖掘揭示了肿瘤-免疫细胞相互作用的分子机制的新见解。在本文中，我们介绍了用于分析整合的临床和生物分子数据的计算工具。具体来说，我们描述了一个用于异构数据类型的数据库，以及包括聚类方法、生存分析以及可视化方法在内的接口生物信息学和统计工具。此外，我们还讨论了与临床和生物分子数据集成相关的一般问题，以及包括生物分子网络重建和数学建模在内的综合数据分析的最新进展。
