title: Prediction of tissue-specific effects of gene knockout on apoptosis in different anatomical structures of human brain.
abstract: BACKGROUND
  An important issue in the target identification for the drug design is the tissue-specific effect of inhibition of target genes. The task of assessing the tissue-specific effect in suppressing gene activity is especially relevant in the studies of the brain, because a significant variability in gene expression levels among different areas of the brain was well documented.
  
  
  RESULTS
  A method is proposed for constructing statistical models to predict the potential effect of the knockout of target genes on the expression of genes involved in the regulation of apoptosis in various brain regions. The model connects the expression of the objective group of genes with expression of the target gene by means of machine learning models trained on available expression data. Information about the interactions between target and objective genes is determined by reconstruction of target-centric gene network. STRING and ANDSystem databases are used for the reconstruction of gene networks. The developed models have been used to analyse gene knockout effects of more than 7,500 target genes on the expression of 1,900 objective genes associated with the Gene Ontology category "apoptotic process". The tissue-specific effect was calculated for 12 main anatomical structures of the human brain. Initial values of gene expression in these anatomical structures were taken from the Allen Brain Atlas database. The results of the predictions of the effect of suppressing the activity of target genes on apoptosis, calculated on average for all brain structures, were in good agreement with experimental data on siRNA-inhibition.
  
  
  CONCLUSIONS
  This theoretical paper presents an approach that can be used to assess tissue-specific gene knockout effect on gene expression of the studied biological process in various structures of the brain. Genes that, according to the predictions of the model, have the highest values of tissue-specific effects on the apoptosis network can be considered as potential pharmacological targets for the development of drugs that would potentially have strong effect on the specific area of the brain and a much weaker effect on other brain structures. Further experiments should be provided in order to confirm the potential findings of the method.
authors.forename: Evgeny D
authors.initials: ED
authors.lastname: Petrovskiy
authors.forename: Olga V
authors.initials: OV
authors.lastname: Saik
authors.forename: Evgeny S
authors.initials: ES
authors.lastname: Tiys
authors.forename: Inna N
authors.initials: IN
authors.lastname: Lavrik
authors.forename: Nikolay A
authors.initials: NA
authors.lastname: Kolchanov
authors.forename: Vladimir A
authors.initials: VA
authors.lastname: Ivanisenko
mesh_terms: D017209:Apoptosis / Q000235:genetics*; D001921:Brain / Q000033:anatomy & histology / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods; D055786:Gene Knockout Techniques; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D009928:Organ Specificity / Q000235:genetics*