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The dysfunctions between two proteins are simultaneously evaluated by their gene expression and correlation in various disease brain regions individually.
In a protein-protein interaction network (PIN), a protein and an interaction between two proteins are represented as a node and a link, respectively.
Most of all, only the pairwise binary interactions between two proteins are considered in PPI, and they are not sufficient to capture real biological processes involving a stable form of proteins grouped according to their biological functions.
Physical interactions between two proteins are the basis for protein complexes and signaling networks, while transcription factors regulate gene transcription by binding to their target DNA sequences in the context of intricate transcriptional regulatory networks.
Given that a majority of all proteins are multi-domain proteins (Jothi et al., 2006) and interactions between two proteins are often characterized by interactions between a pair of constituent domains.
Similar(55)
The functional similarity between two proteins is estimated using encoded information in the GO hierarchies.
The similarity measure between two proteins was quantified by computing the frequencies of a set of functional terms that two proteins share based on semantic similarity measure [46].
If the frequency of shared MIPS functional term between two proteins is less than 4.338, the interacting protein pair must be a positive pair.
Hence, in order to maintain high precision, a stringent domain Tanimoto similarity cut-off of 1 (i.e. requiring a 100% overlap in domain presence and absence between two proteins) was chosen and the top n predicted non-plasmodial targets considered was set to 4 for further analysis.
Interaction between two proteins is represented by a line (edge) connecting two nodes.
Functional similarity between two proteins is determined by using a semantic similarity measure proposed by Couto et al. [34].
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