[网络科学。第一部分:一般肿瘤学]。

Revue medicale de Liege Pub Date : 2024-05-01
Philippe Coucke
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引用次数: 0

摘要

omics级联技术,特别是蛋白质-蛋白质相互作用图谱(相互作用组)所产生的大量数据,使我们能够剖析疾病的复杂性和重叠性,以及疾病的管理。借助网络科学的理论和科学基础,以及人工智能的快速发展,特别是机器学习(具有高速度和高能力),我们今天能够发现新的驱动基因、新的生物标记物、新的与诊断和治疗方法的相互作用(甚至针对个体病人)。它还为预测治疗反应和预防领域开辟了新的前景。在医疗保健领域,人们对新技术的期望特别高,也特别多样化。我们将不厌其烦地介绍肿瘤学领域的一些应用。
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[Network science. Part 1 : in oncology in general].

The overwhelming avalanche of data issued from the omics cascade, and particularly the mapping of protein-protein interaction (interactome), allows us to dissect the complexity and overlapping of diseases, as well as their management. With the help of theoretical and scientific bases issued form network science, as well as the rapid evolution of artificial intelligence, in particular machine learning (with its high speed and capacity), we are able today to uncover new driver genes, new biomarkers, new interactions with diagnostic and therapeutic modalities (even for an individual patient). It also opens new perspectives in the fields of prediction of response to treatment as well as prevention. The expectations are particularly high and diverse in health care. We take stock non-exhaustively on some applications in the field of oncology.

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