Recognition of Multiomics-Based Molecule-Pattern Biomarker for Precise Prediction, Diagnosis, and Prognostic Assessment in Cancer

Bioinformatics Tools for Detection and Clinical Interpretation of Genomic Variations Pub Date : 2019-03-07 DOI:10.5772/INTECHOPEN.84221

Xanquan Zhan, Tian Zhou, Tingting Cheng, Miaolong Lu

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引用次数: 4

Abstract

Cancer is a complex whole-body chronic disease, is involved in multiple causes, multiple processes, and multiple consequences, which are associated with a series of molecular alterations in the different levels of genome, transcriptome, proteome, metabolome, and radiome, with between-molecule mutual interactions. Those molecule-panels are the important resources to recognize the reliable molecular pattern biomarkers for precise prediction, diagnosis, and prognostic assessment in cancer. Pattern recognition is an effective methodology to identify those molecule-panels. The rapid development of computation biology, systems biology, and multiomics is driving the development of pattern recognition to discover reliable molecular pattern biomarkers for cancer treatment. This book chapter addresses the concept of pattern recognition and pattern biomarkers, status of multiomics-based molecular patterns, and future perspective in prediction, diagnosis, and prognostic assessment of a cancer.

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识别基于多组学的分子模式生物标志物用于癌症的精确预测、诊断和预后评估

癌症是一种复杂的全身性慢性疾病，涉及多因、多过程、多后果，与基因组、转录组、蛋白质组、代谢组、放射组等不同水平的一系列分子改变有关，并存在分子间相互作用。这些分子面板是识别可靠的分子模式生物标志物的重要资源，可用于癌症的精确预测、诊断和预后评估。模式识别是一种有效的分子板识别方法。计算生物学、系统生物学和多组学的快速发展正在推动模式识别的发展，以发现可靠的分子模式生物标志物，用于癌症治疗。本章涉及模式识别和模式生物标志物的概念，基于多组学的分子模式的现状，以及癌症预测、诊断和预后评估的未来前景。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Bioinformatics Tools for Detection and Clinical Interpretation of Genomic Variations

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