A two-step framework for inferring direct protein-protein interaction network from AP-MS data
| Autor: | Zengyou He, Feiyang Gu, Can Zhao, Bo Tian |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Computer science Protein-protein interactions Association (object-oriented programming) Systems biology 0206 medical engineering Two step 02 engineering and technology computer.software_genre Chromatography Affinity Protein protein interaction network 03 medical and health sciences Network deconvolution Structural Biology Protein Interaction Mapping False positive paradox Molecular Biology lcsh:QH301-705.5 Mass spectrometry Research Applied Mathematics Scoring methods Computational Biology Affinity purification Computer Science Applications 030104 developmental biology lcsh:Biology (General) Modeling and Simulation Data mining computer 020602 bioinformatics |
| Zdroj: | BMC Systems Biology, Vol 11, Iss S4, Pp 17-25 (2017) BMC Systems Biology |
| ISSN: | 1752-0509 |
| DOI: | 10.1186/s12918-017-0452-y |
| Popis: | Background Affinity purification-mass spectrometry (AP-MS) has been widely used for generating bait-prey data sets so as to identify underlying protein-protein interactions and protein complexes. However, the AP-MS data sets in terms of bait-prey pairs are highly noisy, where candidate pairs contain many false positives. Recently, numerous computational methods have been developed to identify genuine interactions from AP-MS data sets. However, most of these methods aim at removing false positives that contain contaminants, ignoring the distinction between direct interactions and indirect interactions. Results In this paper, we present an initialization-and-refinement framework for inferring direct PPI networks from AP-MS data, in which an initial network is first generated with existing scoring methods and then a refined network is constructed by the application of indirect association removal methods. Experimental results on several real AP-MS data sets show that our method is capable of identifying more direct interactions than traditional scoring methods. Conclusions The proposed framework is sufficiently general to incorporate any feasible methods in each step so as to have potential for handling different types of AP-MS data in the future applications. Electronic supplementary material The online version of this article (doi:10.1186/s12918-017-0452-y) contains supplementary material, which is available to authorized users. |
| Databáze: | OpenAIRE |
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