Koutrouli Mikaela, Karatzas Evangelos, Paez-Espino David, Pavlopoulos Georgios A
Institute for Fundamental Biomedical Research, BSRC "Alexander Fleming", Vari, Greece.
Department of Informatics and Telecommunications, University of Athens, Athens, Greece.
Front Bioeng Biotechnol. 2020 Jan 31;8:34. doi: 10.3389/fbioe.2020.00034. eCollection 2020.
Networks are one of the most common ways to represent biological systems as complex sets of binary interactions or relations between different bioentities. In this article, we discuss the basic graph theory concepts and the various graph types, as well as the available data structures for storing and reading graphs. In addition, we describe several network properties and we highlight some of the widely used network topological features. We briefly mention the network patterns, motifs and models, and we further comment on the types of biological and biomedical networks along with their corresponding computer- and human-readable file formats. Finally, we discuss a variety of algorithms and metrics for network analyses regarding graph drawing, clustering, visualization, link prediction, perturbation, and network alignment as well as the current state-of-the-art tools. We expect this review to reach a very broad spectrum of readers varying from experts to beginners while encouraging them to enhance the field further.
网络是将生物系统表示为不同生物实体之间复杂的二元相互作用或关系集的最常见方式之一。在本文中，我们讨论了基本的图论概念和各种图类型，以及用于存储和读取图的可用数据结构。此外，我们描述了几个网络属性，并强调了一些广泛使用的网络拓扑特征。我们简要提及了网络模式、基序和模型，并进一步评论了生物和生物医学网络的类型及其相应的计算机可读和人类可读文件格式。最后，我们讨论了用于网络分析的各种算法和指标，包括图绘制、聚类、可视化、链接预测、扰动和网络对齐，以及当前的先进工具。我们期望这篇综述能吸引从专家到初学者的广泛读者群体，同时鼓励他们进一步推动该领域的发展。
