Qoku Arber, Katsaouni Nikoletta, Flinner Nadine, Buettner Florian, Schulz Marcel H
German Cancer Consortium (DKTK), partner site Frankfurt/Mainz, a partnership between DKFZ and UCT Frankfurt-Marburg, Germany, Frankfurt am Main, Germany.
German Cancer Research Center (DKFZ), Heidelberg, Germany.
Comput Struct Biotechnol J. 2023 Nov 20;21:5829-5838. doi: 10.1016/j.csbj.2023.11.011. eCollection 2023.
For medicine to fulfill its promise of personalized treatments based on a better understanding of disease biology, computational and statistical tools must exist to analyze the increasing amount of patient data that becomes available. A particular challenge is that several types of data are being measured to cope with the complexity of the underlying systems, enhance predictive modeling and enrich molecular understanding. Here we review a number of recent approaches that specialize in the analysis of multimodal data in the context of predictive biomedicine. We focus on methods that combine different OMIC measurements with image or genome variation data. Our overview shows the diversity of methods that address analysis challenges and reveals new avenues for novel developments.
为了让医学基于对疾病生物学的更深入理解实现个性化治疗的承诺，必须存在计算和统计工具来分析日益增多的可用患者数据。一个特殊的挑战是，为了应对基础系统的复杂性、增强预测建模并丰富分子理解，正在测量多种类型的数据。在此，我们回顾一些近期在预测性生物医学背景下专门用于分析多模态数据的方法。我们专注于将不同的组学测量与图像或基因组变异数据相结合的方法。我们的综述展示了应对分析挑战的方法的多样性，并揭示了新的发展途径。
