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Evolution of Sequence-based Bioinformatics Tools for Protein-protein Interaction Prediction

机译:基于序列的蛋白质 - 蛋白质相互作用预测的生物信息工具的演变

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Protein-protein interactions (PPIs) are the physical connections between two or more proteins via electrostatic forces or hydrophobic effects. Identification of the PPIs is pivotal, which contributes to many biological processes including protein function, disease incidence, and therapy design. The experimental identification of PPIs via high-throughput technology is time-consuming and expensive. Bioinformatics approaches are expected to solve such restrictions. In this review, our main goal is to provide an inclusive view of the existing sequence-based computational prediction of PPIs. Initially, we briefly introduce the currently available PPI databases and then review the state-of-the-art bioinformatics approaches, working principles, and their performances. Finally, we discuss the caveats and future perspective of the next generation algorithms for the prediction of PPIs.
机译:蛋白质 - 蛋白质相互作用(PPI)是通过静电力或疏水效应的两种或更多种蛋白质之间的物理连接。 PPI的鉴定是关键的,这有助于许多生物学过程,包括蛋白质功能,疾病发病率和治疗设计。通过高通量技术的PPI的实验鉴定是耗时和昂贵的。预计生物信息学方法将解决此类限制。在本综述中,我们的主要目标是提供一种包容性的PPI基于序列的计算预测。最初,我们简要介绍了目前可用的PPI数据库,然后审查最先进的生物信息学方法,工作原则及其表演。最后,我们讨论了用于预测PPI的下一代算法的警告和未来的视角。

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