Pathway Prediction in Protein–Protein Interaction Networks Based on Hierarchical Clustering Algorithm
Pathway prediction is vital for understanding biological processes and the mechanism of controlling products synthesis, and for identifying drug targets. Pathway prediction has been become a key challenge in system biology. In this paper, a novel computation algorithm is proposed for predicting the genes in the pathways. Firstly, a formula for computing similarity measure is defined by considering that whether the two proteins are direct interaction or not, and that whether the number of common interaction partners is more significant than random. Secondly, a PPI network is constructed through protein–protein interaction dataset, and the similarity measure of each protein pair is computed. At last, hierarchical clustering algorithm is employed for mining its modular structures, namely, protein clusters. Through mapping proteins to the corresponding genes, we can obtain gene clusters and their pathways in the target species. The proposed method is tested on Escherichia coli k-12. Experimental results have shown the effectiveness and attractiveness of the proposed method.
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Document Type: Research Article
Publication date: August 1, 2013
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- Bionanoscience attempts to harness various functions of biological macromolecules and integrate them with engineering for technological applications. It is based on a bottom-up approach and encompasses structural biology, biomacromolecular engineering, material science, and engineering, extending the horizon of material science. The journal aims at publication of (i) Letters (ii) Reviews (3) Concepts (4) Rapid communications (5) Research papers (6) Book reviews (7) Conference announcements in the interface between chemistry, physics, biology, material science, and technology. The use of biological macromolecules as sensors, biomaterials, information storage devices, biomolecular arrays, molecular machines is significantly increasing. The traditional disciplines of chemistry, physics, and biology are overlapping and coalescing with nanoscale science and technology. Currently research in this area is scattered in different journals and this journal seeks to bring them under a single umbrella to ensure highest quality peer-reviewed research for rapid dissemination in areas that are in the forefront of science and technology which is witnessing phenomenal and accelerated growth.
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