Technology of Informative Feature Selection for Immunosignature Analysis.

The main difficulty in practical work with data obtained via immunosignature analysis is high dimensionality and the presence of a significant number of uninformative or false-informative features due to the specific character of the technology. To ensure practically relevant quality of data analysis and classification, it is necessary to take due account of this specific character. The aim of the study is to create and test the technology for effective reduction of immunosignature data dimensionality, which provides practically relevant and high quality of classification with due regard for the properties of the data obtained. MATERIALS AND METHODS: The study involved the use of two normalized data sets obtained from the public biomedical repository and containing the results of immunosignature analysis.The technology for selecting informative features was proposed within the framework of the study. It consisted of three successive steps: 1) breaking a multiclass task into a series of binary tasks using the "one vs all" strategy; 2) screening of false-informative features is performed for each binary comparison by comparing the values of the median of the sets "one" and "all"; 3) ranking of the remaining features according to their informative value and selection of the most informative ones for each binary comparison.To assess the quality of the proposed technology for informative feature selection, we used the results obtained after application of classification based on the filtered data. Support vector method that proved itself in the problems of high-dimensional data classification was used as a classification model. RESULTS: Effectiveness of the proposed technology for informative feature selection was determined. This technology allows us to provide high quality of classification while significantly reducing the feature space. The number of features eliminated in the second step is approximately 50% for each data set under consideration, which greatly simplifies subsequent data analysis. After the third step, when the feature space is reduced to 15 features, the quality of classification by the macro-average F1-score metric is assessed as 98.9% for the GSE52581 dataset. For the GSE52581 dataset, with the feature space reduced to 266 features, the quality of classification by the macro-average F1-score metric is 91.3%. CONCLUSION: The results of the work demonstrate the promising outlook of the proposed technology for informative feature selection as applied to the data of immunosignature analysis.

[Allele frequency distributions of -174G/C polymorphism in regulatory region of interleukin 6 gene (IL6) in Russian and worldwide populations].

Allele and genotype frequencies of the -174G/C polymorphism (rs1800795) in the regulatory region of the IL6 gene, which encode anti-inflammatory cytokine interleukin 6, were determined in seven populations representing five ethnic groups from the European part of Russia (440 individuals), as well as in small cohorts that represent populations from 24 countries of Africa and Eurasia (365 individuals). The maps of the geographic distribution of the -174G/C allele frequencies were constructed based on personal (22 populations) and the literature data (66 populations), and the data from dbSNP database obtained by the HapMap project (10 populations). The frequency of the -174G allele varied from 45 to 100% and was characterized by nonrandom geographic distribution. These data could reflect the adaptive load of the alleles examined, which was different in different regions of the world. It is suggested that the level of pathogen prevalence is one of the environmental factors that determine different adaptive values of the IL6*--174G/C alleles. This suggestion is supported by a positive correlation between the -174G allele frequency and level of pathogen prevalence calculated based on historical data (R = 0.768; p < 0.0001).

In situ measurements of optical parameters in Lake Baikal with the help of a Neutrino telescope.

We present results of an experiment performed in Lake Baikal at a depth of approximately 1 km. The photomultipliers of an underwater neutrino telescope under construction at this site were illuminated by a distant laser. The experiment not only provided a useful cross-check of the time calibration of the detector but also allowed us to determine inherent optical parameters of the water in a way that was complementary to standard methods. In 1997 we measured an absorption length of 22 m and an asymptotic attenuation length of 18 m. The effective scattering length was measured as 480 m. By use of (cos theta) = 0.95 (0.90) for the average scattering angle, this length corresponds to a geometric scattering length of 24 (48) m.