Reconstruction of Bio-molecular Networks
Network reconstruction is the first step for subsequent network analysis, which is an inverse problem and open issue. In this chapter, we will introduce how to construct bio-molecular networks. Generally speaking, bio-molecular networks can be constructed
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Reconstruction of Bio-molecular Networks
Abstract Network reconstruction is the first step for subsequent network analysis, which is an inverse problem and open issue. In this chapter, we will introduce how to construct bio-molecular networks. Generally speaking, bio-molecular networks can be constructed from four approaches: (1) constructing bio-molecular networks from timely updated online databases or published papers; (2) generating artificial bio-molecular networks based on artificial computer algorithms; (3) inferring biomolecular networks from behavioral data of biological entities via sophisticated mathematical or statistical methods; (4) topological identification of complex systems via complex dynamical network theory. Reconstruction of bio-molecular networks facilitates our further mathematical modeling, dynamical analysis, and statistical analysis on the related life systems.
2.1 Backgrounds Network reconstruction is a typical inverse problem in the area of systems biology and complex networks science. In fact, network reconstruction is the first step for network analysis, it is an interesting and increasingly important scientific topic. Our aim of network reconstruction is to infer the relationships among entities in a system, based on experimental technologies, existing data, mathematical and statistical models or general evolution mechanisms of the system. Approaches of network reconstruction can be roughly classified into the following four cases. Case 1:
Construction of bio-molecular networks based on online databases. Various databases have collected timely updated both experimentally and statistically inferred interaction data among molecules [1–9]. Both physical interaction data and functional interaction data have been collected in the existing databases. Some of the collected data are from existing references that were predicted from mathematical or statistical models, but mostly are from high-throughput technologies. Various high-throughput technologies [10] are ceaselessly developed to experimentally determine the relationships among various biological molecules. Some typical
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020 J. Lü, P. Wang, Modeling and Analysis of Bio-molecular Networks, https://doi.org/10.1007/978-981-15-9144-0_2
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Case 2:
Case 3:
Case 4:
2 Reconstruction of Bio-molecular Networks
methods or platforms to detect PPIs include the standard high-throughput yeast-two-hybrid (Y2H) assays [11], phage display technology, surface plasmon resonance, fluorescence resonance energy transfer, protein chip mass spectrometry technology, co-immunoprecipitation, GST pull-down technology, and CrY2H-seq [12], whereas ChIP-Seq (Chromatin Immunoprecipitation sequencing) and CLIP-Seq (cross-linkingimmunoprecipitation and high-throughput sequencing (HTS)) can be used to detect the interaction between proteins and DNAs or RNAs. Evolutionary mechanisms of the system were known, how to generate networks that follow t
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