Abstract
Predicting protein-protein interactions (PPI) is an important problem in computational biology and has diverse applications. In this work, an attempt is made to predict the existence of protein-protein interactions in the context of a system of blood tissue cell modelled as a multi-layer PPI network. The effect of the interdependence between the layers in the network on the prediction of PPI is explored by formulating this as a link prediction problem. The hierarchical features produced by multi-layer node embedding algorithms are captured using a weighted addition method which results in enriched node features. These features are visualised and then used to perform a link-prediction task. The obtained results are compared to those of existing techniques. It is found that multi-layer node embedding that captures inter-layer dependencies perform better than single layer algorithms applied on the multi-layer network even on a limited data set constrained by simplifying assumptions and limited computational resources.
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Kapadia, P., Khare, S., Priyadarshini, P., Das, B. (2019). Predicting Protein-Protein Interaction in Multi-layer Blood Cell PPI Networks. In: Luhach, A., Jat, D., Hawari, K., Gao, XZ., Lingras, P. (eds) Advanced Informatics for Computing Research. ICAICR 2019. Communications in Computer and Information Science, vol 1076. Springer, Singapore. https://doi.org/10.1007/978-981-15-0111-1_22
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DOI: https://doi.org/10.1007/978-981-15-0111-1_22
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