• The Journal of the Korea Contents Association
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• v.8 no.6
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• pp.74-81
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• 2008

Protein interaction network contains a small number of highly connected protein, denoted hub and many destitutely connected proteins. Recently, several studies described that a hub protein is more likely to be essential than a non-hub protein. This phenomenon called as a centrality-lethality rule. This nile is widely credited to exhibit the importance of hub proteins in the complex network and the significance of network architecture as well. To confirm whether the rule is accurate, we Investigated all protein interaction DBs of yeast in the public sites such as Uetz, Ito, MIPS, DIP, SGB, and BioGRID. Interestingly, the protein network shows that the rule is correct in lower scale DBs (e.g., Uetz, Ito, and DIP) but is not correct in higher scale DBs (e.g., SGD and BioGRID). We are now analyzing the features of networks obtained from the SGD and BioGRD and comparing those of network from the DIP.

• BMB Reports
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• v.38 no.1
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• pp.97-103
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• 2005

Under the condition of expression of $\lambda$ P protein at lethal level, the oriC DNA-binding activity is significantly affected in wild-type E. coli but not in the rpl mutant. In purified system, the $\lambda$ P protein inhibits the binding of both oriC DNA and ATP to the wild-type DnaA protein but not to the rpl DnaA protein. We conclude that the $\lambda$ P protein inhibits the binding of oriC DNA and ATP to the wild-type DnaA protein, which causes the inhibition of host DNA synthesis initiation that ultimately leads to bacterial death. A possible beneficial effect of this interaction of $\lambda$ P protein with E. coli DNA initiator protein DnaA for phage DNA replication has been proposed.

• The KIPS Transactions:PartD
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• v.19D no.1
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• pp.21-28
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• 2012

Predication of protein interaction sites for monomer structures can reduce the search space for protein docking and has been regarded as very significant for predicting unknown functions of proteins from their interacting proteins whose functions are known. In the other hand, the prediction of interaction sites has been limited in crystallizing weakly interacting complexes which are transient and do not form the complexes stable enough for obtaining experimental structures by crystallization or even NMR for the most important protein-protein interactions. This work reports the calculation of 3D surface patches of complex structures and their properties and a machine learning approach to build a predictive model for the 3D surface patches in interaction and non-interaction sites using support vector machine. To overcome classification problems for class imbalanced data, we employed an under-sampling technique. 9 properties of the patches were calculated from amino acid compositions and secondary structure elements. With 10 fold cross validation, the predictive model built from SVM achieved an accuracy of 92.7% for classification of 3D patches in interaction and non-interaction sites from 147 complexes.

• BMB Reports
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• v.34 no.5
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• pp.452-456
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• 2001

Surface plasmon resonance has been used for a biospecific interaction analysis between two macromolecules in real time. Determination of an antibody that is capable of specifically interacting with the native form of antigen is very useful for many biological and medical applications. Twenty monoclonal antibodies against the $\alpha$ subunit of E. coli DNA polymerase III were screened for specifically recognizing the native form of protein using surface plasmon resonance. Only four monoclonal antibodies among them specifically recognized the native $\alpha$ protein, although all of the antibodies were able to specifically interact with the denatured $\alpha$ subunit. These antibodies failed to interfere with the interaction between the $\tau$ and $\alpha$ subunits that were required for dimerization of the two polymerases at the DNA replication fork. This real-time analysis using surface plasmon resonance provides an easy method to screen antibodies that are capable of binding to the native form of the antigen molecule and determine the biological interaction between the two molecules.

• Genomics & Informatics
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• v.5 no.3
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• pp.133-136
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• 2007

The Gene Set network viewer (GSnet) visualizes the functional enrichment of a given gene set with a protein interaction network and is implemented as a plug-in for the Cytoscape platform. The functional enrichment of a given gene set is calculated using a hypergeometric test based on the Gene Ontology annotation. The protein interaction network is estimated using public data. Set operations allow a complex protein interaction network to be decomposed into a functionally-enriched module of interest. GSnet provides a new framework for gene set analysis by integrating a priori knowledge of a biological network with functional enrichment analysis.

• Animal cells and systems
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• v.6 no.3
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• pp.277-282
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• 2002

Topoisomearse II is an essential enzyme in all organisms with several independent roles in DNA metabolism. Recently, it has been demonstrated that the C-terminal region of topoisomerases II is associated with hetero-logous protein-protein interactions in human and yeast. In this study, we identified that RTP1, a rat homologue of EIA binding protein BS69, is another topoisomerae II interacting protein by yeast two-hybrid screening. RTP1 has an E1A-binding domain and a MYND motif, which are known to be required for transcriptional regulation by binding to other proteins and interaction with the leucine zipper motif of topoisomerase II. The physical interaction between RTP1 and topoisomerase ll$\alpha$ was examined by GST pull-down assay in vitro. The expression level of RTP1 peaks in S phase as that of topoisomerase ll$\alpha$. These results suggest that the interaction between topoisomerase ll$\alpha$ and RTP1 might play an important role in regulating the transcription of genes involved in DNA metabolism in higher eukaryotes.

• Genomics & Informatics
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• v.2 no.2
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• pp.99-106
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• 2004

In this paper we introduce PubMiner, an intelligent machine learning based text mining system for mining biological information from the literature. PubMiner employs natural language processing techniques and machine learning based data mining techniques for mining useful biological information such as protein­protein interaction from the massive literature. The system recognizes biological terms such as gene, protein, and enzymes and extracts their interactions described in the document through natural language processing. The extracted interactions are further analyzed with a set of features of each entity that were collected from the related public databases to infer more interactions from the original interactions. An inferred interaction from the interaction analysis and native interaction are provided to the user with the link of literature sources. The performance of entity and interaction extraction was tested with selected MEDLINE abstracts. The evaluation of inference proceeded using the protein interaction data of S. cerevisiae (bakers yeast) from MIPS and SGD.

• CELLMED
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• v.4 no.1
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• pp.6.1-6.12
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• 2014

Anthrax is the deadly disease for human being caused by Bacillus anthracis. Instantaneous research work on the mode of infection of the organism revealed that different proteases are involved in different steps of pathogenesis. Present study reports the in silico characterization and the detection of pathogenic proteases involved in anthrax infection through protein-protein interaction. A total of 13 acid, 9 neutral, and 1 alkaline protease of Bacillus anthracis were selected for analysing the physicochemical parameter, the protein superfamily and family search, multiple sequence alignment, phylogenetic tree construction, protein-protein interactions and motif finding. Among the 13 acid proteases, 10 were found as extracellular enzymes that interact with immune inhibitor A (InhA) and help the organism to cross the blood brain barrier during the process of infection. Multiple sequence alignment of above acid proteases revealed the position 368, 489, and 498-contained 100% conserved amino acids which could be used to deactivate the protease. Among the groups analyzed, only acid protease were found to interact with InhA, which indicated that metalloproteases of acid protease group have the capability to develop pathogenesis during B. anthracis infection. Deactivation of conserved amino acid position of germination protease can stop the sporulation and germination of B anthracis cell. The detailed interaction study of neutral and alkaline proteases could also be helpful to design the interaction network for the better understanding of anthrax disease.

• Asian-Australasian Journal of Animal Sciences
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• v.7 no.2
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• pp.207-212
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• 1994

Effects of dietary cellulose and protein levels on nutrient utilization in chickens were investigated. Four experimental diets containing 5% (low cellulose) or 20% (high cellulose) cellulose in combination with 10% (low protein) or 20% (high protein) protein of 70 g/day were alternatively forced-fed to eight colostomized White Leghorn cockerels once a day to make $4{\times}4$ Latin-square design. The digestibilities of DM and energy decreased with the increase in cellulose level, but not affected by dietary protein level. Ether extract digestibility was higher in the high cellulose diets than in the low cellulose protein level. Ether extract digestibility was higher in the high cellulose diets than in the low cellulose diets. The digestibility of nitrogen free extract had the same trend with the digestibility of DM and energy. The digestibility of acid detergent fiber was not so much different among the diets, but the NDF digestibility was lower in the high cellulose diets than in the low cellulose diets, due to the low hemicellulose digestibility. The true digestibility of protein was influenced by both of the dietary protein and cellulose levels, and their interaction was found. The dietary protein level affected the biological value of protein but the dietary cellulose level did not, and consequently the biological value of protein in the low protein diets was lower than in the high protein diets.

• Korean Journal of Veterinary Service
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• v.25 no.4
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• pp.333-346
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• 2002

We previously reported that the equine herpesvirus type 1(EHV-1) immediate-early protein(IE protein) physically interacts with the general transcription factor human TFIIB(Jang et al, J Virol 75：10219-10230, 2001). The interaction between the IE protein and TFIIB is necessary for the IE protein to efficiently transactivate the early TK and late IR5 EHV-1 promoters. A panel of deletion and truncation mutants of the TFIIB gene was constructed and employed in protein-binding assays to map the IE protein-binding domain within TFIIB. Evidence is presented that the first direct repeat of TFIIB interacts specifically with the EHV-1 IE protein.