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In silico methods are often used for predicting pharmacokinetic properties of drugs due to their simplicity and cost-effectiveness. This study evaluates the penetration of 83 active pharmaceutical ingredients into human breast milk with an experimental milk-to-plasma ratio (M/P) obtained from the literature. Multiple linear regression (MLR), partial least squares (PLS) and random forest (RF) regression methods were compared to uncover the relationship between physicochemical, pharmacokinetic and membrane crossing properties of active pharmaceutical ingredients (APIs) using their rapid reference measurement value (R(f)values), thin-layer chromatography (TLC) data from albumin-impregnated plates. Molecular descriptors of APIs proven to be important for their crossing into breast milk, including protein binding, ionisation state and lipophilicity and TLC data, have been included in the development of the prediction models. The best regression results were achieved by MLR (r(2) = 0.83 andr(2) = 0.86,n= 28) and RF (r(2) = 0.85,n= 58). In addition, the discriminant function analysis (DFA) was performed on acidic, basic and neutral drugs separately and showed a prediction accuracy of 93%, with M/P included as the discriminating variable.

The relevance of the study is conditioned by the need of computer program development which allow to transliterate texts from Cyrillic graphics during the operation in non-Russian systems. During transliteration a text written with the use of a particular alphabet, is presented by the alphabet of another system. The correspondence of only two alphabet letters is usually taken into account. However, during the transliteration of living languages they try to take into account the sound aspect in order not to detach a word from its live-sounding form. Thus, they transliterate not an alphabet, but the graphics adopted in this language system. Modern Tatar language has Cyrillic graphics. In this regard, the article shows the process of software development, which allows you to convert a text written in Tatar language using Cyrillic symbols into the Latin symbols. The principle of conversion is proposed, based on etymology. Original Tatar words are proposed to convert according to phonetic principle, and the borrowed words are proposed to convert according to transliteration rules. In order to determine the origin of a Tatar word it is proposed to use the following algorithms: digram analysis, combined analysis and search. An algorithmic model of conversion was developed. The software designed by the authors allows to transliterate native Tatar words nowadays.

© 2017 Association for Computing Machinery. The paper discusses the main principles and practical aspects of implementing a new bilingual lexical resource - the Russian-Tatar thesaurus on socio-political and IT issues. This thesaurus is developed on the basis of the Russian RuThes thesaurus format which is built as a hierarchy of concepts viewed as units of thought, with each concept linked to a set of language expressions that refer to it in texts (text entries). The paper discusses general methodology of translating concept names and their text entries, as well as ways of reflecting the specificity of the Tatar lexical-semantic system.

© 2017, Springer International Publishing AG. The paper is dedicated to the problem of grammatical ambiguity in the Tatar National Corpus and describes the methodology and software used for automation of the disambiguation process. Grammatical ambiguity is widely represented in agglutinative languages like Turkic or Finno-Ugric. Disambiguation in the corpus is based on the context-oriented classification of ambiguity types which has been carried out on corpus data in the Tatar language for the first time. In this study the corpus is used as a source for the research and at the same time as a destination for implementing the results. The grammatical ambiguity types are detected automatically using the finite-state morphological analyzer and then classified. In order to build up the grammatically disambiguated subcorpus, a special software module was developed. It searches for ambiguous tokens in the corpus, collects statistical information and allows creating and implementing the formal context-based disambiguation rules for different ambiguity types.

© 2017, Springer International Publishing AG. The paper is dedicated to the problem of grammatical ambiguity in the Tatar National Corpus and describes the methodology and software used for automation of the disambiguation process. Grammatical ambiguity is widely represented in agglutinative languages like Turkic or Finno-Ugric. Disambiguation in the corpus is based on the context-oriented classification of ambiguity types which has been carried out on corpus data in the Tatar language for the first time. In this study the corpus is used as a source for the research and at the same time as a destination for implementing the results. The grammatical ambiguity types are detected automatically using the finite-state morphological analyzer and then classified. In order to build up the grammatically disambiguated subcorpus, a special software module was developed. It searches for ambiguous tokens in the corpus, collects statistical information and allows creating and implementing the formal context-based disambiguation rules for different ambiguity types.

The relevance of the study is conditioned by the need of computer program development which allow to transliterate texts from Cyrillic graphics during the operation in non-Russian systems. During transliteration a text written with the use of a particular alphabet, is presented by the alphabet of another system. The correspondence of only two alphabet letters is usually taken into account. However, during the transliteration of living languages they try to take into account the sound aspect in order not to detach a word from its live-sounding form. Thus, they transliterate not an alphabet, but the graphics adopted in this language system. Modern Tatar language has Cyrillic graphics. In this regard, the article shows the process of software development, which allows you to convert a text written in Tatar language using Cyrillic symbols into the Latin symbols. The principle of conversion is proposed, based on etymology. Original Tatar words are proposed to convert according to phonetic principle, and the borrowed words are proposed to convert according to transliteration rules. In order to determine the origin of a Tatar word it is proposed to use the following algorithms: digram analysis, combined analysis and search. An algorithmic model of conversion was developed. The software designed by the authors allows to transliterate native Tatar words nowadays.