title: Optimization and Corroboration of the Regulatory Pathway of p42.3 Protein in the Pathogenesis of Gastric Carcinoma.
abstract: OBJECTIVE
  To optimize and verify the regulatory pathway of p42.3 in the pathogenesis of gastric carcinoma (GC) by intelligent algorithm.
  
  
  METHODS
  Bioinformatics methods were used to analyze the features of structural domain in p42.3 protein. Proteins with the same domains and similar functions to p42.3 were screened out for reference. The possible regulatory pathway of p42.3 was established by integrating the acting pathways of these proteins. Then, the similarity between the reference proteins and p42.3 protein was figured out by multiparameter weighted summation method. The calculation result was taken as the prior probability of the initial node in Bayesian network. Besides, the probability of occurrence in different pathways was calculated by conditional probability formula, and the one with the maximum probability was regarded as the most possible pathway of p42.3. Finally, molecular biological experiments were conducted to prove it.
  
  
  RESULTS
  In Bayesian network of p42.3, probability of the acting pathway "S100A11→RAGE→P38→MAPK→Microtubule-associated protein→Spindle protein→Centromere protein→Cell proliferation" was the biggest, and it was also validated by biological experiments.
  
  
  CONCLUSIONS
  The possibly important role of p42.3 in the occurrence of gastric carcinoma was verified by theoretical analysis and preliminary test, helping in studying the relationship between p42.3 and gastric carcinoma.
authors.affiliation: Zhengzhou Central Hospital, Zhengzhou, Henan 450007, China.
authors.forename: Yibin
authors.initials: Y
authors.lastname: Hao
authors.affiliation: Department of Pharmacology, School of Basic Medicine, Zhengzhou University, Zhengzhou, Henan 450001, China.
authors.forename: Tianli
authors.initials: T
authors.lastname: Fan
authors.affiliation: Department of Oncology, The First Affiliated Hospital, College of Medicine of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
authors.forename: Kejun
authors.initials: K
authors.lastname: Nan
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001665:Binding Sites; D018797:Cell Cycle Proteins / Q000235:genetics / Q000502:physiology*; D045744:Cell Line, Tumor; D049109:Cell Proliferation; D019295:Computational Biology; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008024:Ligands; D008962:Models, Theoretical; D009687:Nuclear Proteins; D011336:Probability; D017434:Protein Structure, Tertiary; D013274:Stomach Neoplasms / Q000503:physiopathology*
chemical_list: D018797:Cell Cycle Proteins; D008024:Ligands; D009687:Nuclear Proteins; C000607889:SAPCD2 protein, human