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Predicting Protein-protein Interaction and Study on hub Protein Classification and Interaction Law
Author: QinZuo
Tutor: CaiLu
School: Inner Mongolia University of Science and Technology
Course: Genetics
Keywords: Protein Interaction Bayesian networks Hub proteins Bias
CLC: Q51
Type: Master's thesis
Year: 2010
Downloads: 69
Quote: 0
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Abstract
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Post-genomic era , and its network of protein-protein interaction systems biology research has become an important task . Development theory methods to predict protein interactions is not only a useful complement to experimental methods , more research is essentially the mechanism of protein-protein interactions . Research on protein networks can understand the overall evolution of life and life functions and other aspects of the rules and characteristics . Protein interacts directly dependent on its spatial structure, protein secondary structure as the basic elements of its spatial structure should contain information about the interaction . This article is based on the two interacting protein structural information , propose a Bayesian classifier protein interaction prediction model . Yeast , human data and open test on mice , fruit flies independent set test to obtain preliminary forecast of 59.16% and 59.85% accuracy , which indicates that the protein secondary structure information and Bayesian classifier can indeed be used protein interaction prediction . Protein interaction networks , Hub protein as the number of connections to the higher category proteins life activities exercised in a more important function. However, relying solely on the number of connections does not accurately reflect the proteins in the biology of the true status of the network , the number of connections similar Hub proteins in biological networks may play an important role . Gene ontology database based on the biological annotation information , using the X -means clustering method Hub proteins into systems, components and processes Hub categories ; Hub protein consisting of these three types of sub-networks , and found that the system Hub and non- Hub protein sub-network distribution, while the components and processes Hub Hub subnetworks obvious modularity ; further described in the introduction of various types of interactions between proteins tendency Hub parameter analysis showed that: between three Hub proteins ( including the same class Hub -protein ) , non- Hub Hub protein protein interactions with a strong tendency , which in turn three Hub Hub between proteins and non- protein , non- protein interactions within Hub tendency weak.
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CLC: > Biological Sciences > Biochemistry > Protein
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