基于GeIS的神经母细胞瘤风险评估概念模型

Verónica Burriel, José Fabián Reyes Román, Ana Heredia Casanoves, Carlos Iñiguez-Jarrín, Ana León
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引用次数: 8

摘要

神经母细胞瘤等罕见和复杂疾病的风险评估需要对跨学科数据进行有效的管理。基因组检测的最新进展揭示了新的诊断靶点,其存储和分析正成为一个巨大的挑战。使用概念模型(CM)来定义和构建神经母细胞瘤结构域,作为确定诊断疾病所需信息的基础。基于CM的基因组信息系统(GeIS),极大地促进了异构和分散基因组数据的整合和管理。正确利用经过验证的数据集可以对神经母细胞瘤患者进行有效和早期的风险评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GeIS based on Conceptual Models for the risk assessment of Neuroblastoma
Risk assessment of rare and complex diseases such as Neuroblastoma requires an efficient management of interdisciplinary data. Recent advances in genomic testing are revealing new diagnosis targets whose storage and analysis is becoming a big challenge. The use of Conceptual Models (CM) defining and structuring Neuroblastoma domain serves as a basis to determine the information required for diagnosing the disease. A Genomic Information System (GeIS) built upon a CM, greatly facilitate the integration and management of the heterogeneous and dispersed genomic data. The correct exploitation of the validated dataset leads to an efficient and early risk assessment for patients with Neuroblastoma.
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