Using Biological Networks in Protein Function Prediction and Gene Expression Analysis

Q3 Mathematics
L. Wong
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引用次数: 3

Abstract

Abstract While sequence homology search has been the main workhorse in protein function prediction, it is not applicable to a significant portion of novel proteins that do not have informative homologues in sequence databases. Similarly, while statistical tests and learning algorithms based purely on gene expression profiles have been popular for analyzing disease samples, critical issues remain in the understanding of diseases based on the differentially expressed genes suggested by these methods. In the past decade, a large number of databases providing information on various types of biological networks have become available. These databases make it possible to tackle these and other biological problems in novel ways. This paper presents a review of biological network databases and approaches to protein function prediction and gene expression profile analysis that are based on biological networks.
生物网络在蛋白质功能预测和基因表达分析中的应用
虽然序列同源性搜索一直是蛋白质功能预测的主要手段,但它并不适用于在序列数据库中没有信息同源性的新蛋白质的很大一部分。同样,虽然纯粹基于基因表达谱的统计测试和学习算法在分析疾病样本方面已经很流行,但关键问题仍然是基于这些方法所建议的差异表达基因来理解疾病。在过去的十年中,已经出现了大量提供各种类型生物网络信息的数据库。这些数据库使得以新颖的方式解决这些和其他生物学问题成为可能。本文综述了生物网络数据库以及基于生物网络的蛋白质功能预测和基因表达谱分析方法。
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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来源期刊
Internet Mathematics
Internet Mathematics Mathematics-Applied Mathematics
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