Lawrence Berkeley Labs, DOE Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA 94598, USA.
University of Thessaly, Department of Computer Science and Biomedical Informatics, Papasiopoulou 2-4, Lamia, 35100, Greece.
Gigascience. 2018 Apr 1;7(4):1-31. doi: 10.1093/gigascience/giy014.
The latest advances in high-throughput techniques during the past decade allowed the systems biology field to expand significantly. Today, the focus of biologists has shifted from the study of individual biological components to the study of complex biological systems and their dynamics at a larger scale. Through the discovery of novel bioentity relationships, researchers reveal new information about biological functions and processes. Graphs are widely used to represent bioentities such as proteins, genes, small molecules, ligands, and others such as nodes and their connections as edges within a network. In this review, special focus is given to the usability of bipartite graphs and their impact on the field of network biology and medicine. Furthermore, their topological properties and how these can be applied to certain biological case studies are discussed. Finally, available methodologies and software are presented, and useful insights on how bipartite graphs can shape the path toward the solution of challenging biological problems are provided.
过去十年中高通量技术的最新进展使得系统生物学领域得到了显著扩展。如今，生物学家的研究重点已经从单个生物成分的研究转移到了更大规模的复杂生物系统及其动态的研究。通过发现新的生物实体关系，研究人员揭示了关于生物功能和过程的新信息。图广泛用于表示生物实体，如蛋白质、基因、小分子、配体等，以及节点及其在网络中的边缘连接。在这篇综述中，特别关注二部图的可用性及其对网络生物学和医学领域的影响。此外，还讨论了它们的拓扑性质以及如何将这些性质应用于某些生物学案例研究。最后，介绍了现有的方法和软件，并就二部图如何为解决具有挑战性的生物学问题提供解决方案提供了有用的见解。
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