With the rapid technological advances in acquiring data from diverse platforms in cancer research, numerous large scale omics and imaging data sets have become available, providing high-resolution views and multifaceted descriptions of biological systems. Simultaneous analysis of such multimodal data sets is an important task in integrative systems biology. The main challenge here is how to integrate them to extract relevant and meaningful information for a given problem. The multimodal data contains more information and the combination of multimodal data may potentially provide a more complete and discriminatory description of the intrinsic characteristics of pattern by producing improved system performance than individual modalities. In this regard, some recent advances in multimodal big data analysis for cancer diagnosis are reported in this article.

中文翻译：

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多模式大数据分析在癌症诊断中的最新进展

随着从癌症研究的各种平台获取数据的快速技术进步，已经有了许多大规模的组学和成像数据集，它们提供了生物系统的高分辨率视图和多方面的描述。此类多模式数据集的同时分析是集成系统生物学中的重要任务。这里的主要挑战是如何将它们集成在一起，以提取针对给定问题的有意义的信息。多模式数据包含更多信息，并且多模式数据的组合可能通过产生比单个模式更高的系统性能来潜在地提供模式的固有特性的更完整和更具歧视性的描述。在这方面，