Supervised selective kernel fusion for membrane protein prediction

Membrane protein prediction is a significant classification problem, requiring the integration of data derived from different sources such as protein sequences, gene expression, protein interactions etc. A generalized probabilistic approach for combining different data sources via supervised selective kernel fusion was proposed in our previous papers. It includes, as particular cases, SVM, Lasso SVM, Elastic Net SVM and others. In this paper we apply a further instantiation of this approach, the Supervised Selective Support Kernel SVM and demonstrate that the proposed approach achieves the top-rank position among the selective kernel fusion variants on benchmark data for membrane protein prediction. The method differs from the previous approaches in that it naturally derives a subset of “support kernels” (analogous to support objects within SVMs), thereby allowing the memory-efficient exclusion of significant numbers of irrelevant kernel matrixes from a decision rule in a manner particularly suited to membrane protein prediction

Metallurgical Properties and Phase Transformations of Barium-Strontium Modifier

Metallurgical properties and phase transformations of barium-strontium modifier were tested in laboratory conditions resembling steel processing in furnace and ladle. When heating barium-strontium modifier start of melting, kinetics of decomposition, phase and structure transformation were studied. The concentrate under consideration has been revealed to be a complex mineral compound containing barytocalcite, calcite, calciostrontianite, dolomite and siderite. The reaction kinetics of decomposing mineral components of barium-strontium modifier to oxides does not considerably affect slag formation in conditions of out-of-furnace steel processing

Annual dynamics of parameters of physical development of boys and girls aged 18 and 19

The questions concerning the terms of juvenile age body measurement as well as body composition variability remain relevance and academic novelty. Such studies results data are essential for systematic analysis on secular trend of young generation development.Material and methods. Longitudinal study of physical development (length, body weight, muscle and fat component) of boys and girls aged 18 and 19, studying at 1–2 courses of university and living in a dormitory has been applied.Results and discussion. In boys and girls aged 18–19, body length and body weight have increased for 1 year on average by 1.5 and 0.9 cm and by 1.3 and 1.2 kg, respectively. In 22.6 % of boys and 54.8 % of girls body length does not change. The annual changes in the fat component are not reliable, whereas the muscle component increases significantly by 3 % in boys and by 0.8 % in girls. Students living in a dormitory often experience a lack of night sleep, they do not have enough physical activity, consume not enough calories, valuable proteins and fats. Because of this, physical development may deteriorate.Conclusions. The annual variability of the indicators of physical development of students aged 18–19 years indicates the ongoing processes of growth and development, which are more pronounced in boys, in girls there is a tendency to stabilize the length of the body. Knowledge about the sensitivity of the body of first-year students mastering the requirements for studying at a university and independent living in a dormitory is necessary for the organization of work on pedagogical support during the adaptation of first-year students

Clustering as a criterion for the success of modern industrial enterprises

The paper reveals the problems of the use of clusters as an important factor of innovative development of Russian enterprises and territorial entities delineated a theoretical basis for the existence of territorial formations, showing their relationship with the clusters displayed in the cluster's functioning as an open system. All the more important in the formation of innovation territorial entities in Russia acquire the cluster structure based on cooperation of enterprises, financial institutions, educational institutions etc. In the developed countries have long had and continue to have such structures in various industries. In the works of famous foreign scientists clearly defined theoretical bases of formation and functioning of clusters, use cluster models to ensure the competitiveness of the economy, their advantages and disadvantages. Foreign experience can be useful to develop a national strategy for clustering of Russia, with a comprehensive study of its socioeconomic development. These tasks at this stage be a priority for Central and local public authorities. Issues related to the principles of clusters, innovation economy, have been studied by many scientists, both Russian and foreign. In published works, the essence of cluster analysis, given the definition of "cluster" classification of clusters, the role of innovative development of economy, experience of the use of cluster models, etc

Изучение закономерностей синтеза пропиленкарбоната взаимодействием пропиленгликоля с карбамидом

Objectives. Cyclic carbonates are important products of organic synthesis, which are widely used as solvents, catalysts, and reagents for the production of various compounds (in particular, urethane-containing polymers) by the non-isocyanate method. The process of carbamide alcoholysis with polybasic alcohols is a promising method for the synthesis of cyclic carbonates. The purpose of this study is to determine the reaction conditions for the interaction of propylene glycol with carbamide in the presence of zinc acetate as a catalyst.Methods. We conducted experiments to study the synthesis of propylene carbonate in a batch laboratory apparatus. Moreover, we analyzed the starting reagents and final products using gas–liquid chromatography.Results. We studied the synthesis of propylene carbonate by carbamide alcoholysis with propylene glycol in the presence of a catalyst (zinc acetate) by varying the following parameters: initial molar ratio of propylene glycol/carbamide = (0.5–5):1, synthesis temperature 130–190°С, reagent residence time in the reactor 0.5–4 h, and the catalyst amount in the reaction mixture 0–1.5 wt %.Conclusions. We determined the technological parameters of propylene carbonate synthesis in a batch reactor. Moreover, we showed that the process allowed the production of propylene carbonate with a sufficiently high yield of 80%—at the initial molar ratio of propylene glycol/ carbamide = 3:1, temperature 170°C, and residence time 2 h.Цели. Циклические карбонаты являются важными продуктами органического синтеза, которые находят широкое применение в качестве растворителей, катализаторов и реагентов для получения ряда соединений, в частности, уретансодержащих полимеров неизоцианатным методом. Одним из перспективных методов их синтеза является процесс алкоголиза карбамида многоосновными спиртами. Цель данной работы – определение условий реакции взаимодействия пропиленгликоля с карбамидом в присутствии ацетата цинка в качестве катализатора.Методы. Экспериментальное исследование процесса синтеза пропиленкарбоната на лабораторной установке периодического действия. Анализ исходных реагентов и полученных продуктов с использованием газожидкостной хроматографии.Результаты. Изучены закономерности получения пропиленкарбоната алкоголизом карбамида пропиленгликолем в присутствии катализатора (ацетата цинка) при варьировании основных параметров процесса в следующих диапазонах: начальное молярное соотношение реагентов пропиленгликоль/карбамид составляло (0.5–5):1, температура синтеза 130–190 °С, время пребывания реагентов в реакторе 0.5–4 ч, содержание катализатора в реакционной смеси 0–1.5 масс. %.Выводы. Рекомендованы технологические параметры синтеза пропиленкарбоната, протекающего в реакторе периодического действия. Показано, что осуществление процесса при начальном молярном соотношении пропиленгликоля и карбамида 3:1, при температуре 170 °С и времени пребывания 2 ч позволяет получать пропиленкарбонат с достаточно высоким выходом – 80%

Combining Structure and Sequence Information Allows Automated Prediction of Substrate Specificities within Enzyme Families

An important aspect of the functional annotation of enzymes is not only the type of reaction catalysed by an enzyme, but also the substrate specificity, which can vary widely within the same family. In many cases, prediction of family membership and even substrate specificity is possible from enzyme sequence alone, using a nearest neighbour classification rule. However, the combination of structural information and sequence information can improve the interpretability and accuracy of predictive models. The method presented here, Active Site Classification (ASC), automatically extracts the residues lining the active site from one representative three-dimensional structure and the corresponding residues from sequences of other members of the family. From a set of representatives with known substrate specificity, a Support Vector Machine (SVM) can then learn a model of substrate specificity. Applied to a sequence of unknown specificity, the SVM can then predict the most likely substrate. The models can also be analysed to reveal the underlying structural reasons determining substrate specificities and thus yield valuable insights into mechanisms of enzyme specificity. We illustrate the high prediction accuracy achieved on two benchmark data sets and the structural insights gained from ASC by a detailed analysis of the family of decarboxylating dehydrogenases. The ASC web service is available at http://asc.informatik.uni-tuebingen.de/

A Genome Scan for Positive Selection in Thoroughbred Horses

Thoroughbred horses have been selected for exceptional racing performance resulting in system-wide structural and functional adaptations contributing to elite athletic phenotypes. Because selection has been recent and intense in a closed population that stems from a small number of founder animals Thoroughbreds represent a unique population within which to identify genomic contributions to exercise-related traits. Employing a population genetics-based hitchhiking mapping approach we performed a genome scan using 394 autosomal and X chromosome microsatellite loci and identified positively selected loci in the extreme tail-ends of the empirical distributions for (1) deviations from expected heterozygosity (Ewens-Watterson test) in Thoroughbred (n = 112) and (2) global differentiation among four geographically diverse horse populations (FST). We found positively selected genomic regions in Thoroughbred enriched for phosphoinositide-mediated signalling (3.2-fold enrichment; P<0.01), insulin receptor signalling (5.0-fold enrichment; P<0.01) and lipid transport (2.2-fold enrichment; P<0.05) genes. We found a significant overrepresentation of sarcoglycan complex (11.1-fold enrichment; P<0.05) and focal adhesion pathway (1.9-fold enrichment; P<0.01) genes highlighting the role for muscle strength and integrity in the Thoroughbred athletic phenotype. We report for the first time candidate athletic-performance genes within regions targeted by selection in Thoroughbred horses that are principally responsible for fatty acid oxidation, increased insulin sensitivity and muscle strength: ACSS1 (acyl-CoA synthetase short-chain family member 1), ACTA1 (actin, alpha 1, skeletal muscle), ACTN2 (actinin, alpha 2), ADHFE1 (alcohol dehydrogenase, iron containing, 1), MTFR1 (mitochondrial fission regulator 1), PDK4 (pyruvate dehydrogenase kinase, isozyme 4) and TNC (tenascin C). Understanding the genetic basis for exercise adaptation will be crucial for the identification of genes within the complex molecular networks underlying obesity and its consequential pathologies, such as type 2 diabetes. Therefore, we propose Thoroughbred as a novel in vivo large animal model for understanding molecular protection against metabolic disease

A class of evolution-based kernels for protein homology analysis: a generalization of the PAM model

There are two desirable properties that a pair-wise similarity measure between amino acid sequences should possess in order to produce good performance in protein homology analysis. First, it is the presence of kernel properties that allow using popular and well-performing computational tools designed for linear spaces, like SVM and k-means. Second, it is very important to take into account common evolutionary descent of homologous proteins. However, none of the existing similarity measures possesses both of these properties at once. In this paper, we propose a simple probabilistic evolution model of amino acid sequences that is built as a straightforward generalization of the PAM evolution model of single amino acids. This model produces a class of kernel functions each of which is computed as the likelihood of the hypothesis that both sequences are results of two independent evolutionary transformations of a hidden common ancestor under some specific assumptions on the evolution mechanism. The proposed class of kernels is rather wide and contains as particular subclasses not only the family of J.-P Vert’s local alignment kernels, whose algebraic structure was introduced without any evolutionary motivation, but also some other families of local and global kernels. We demonstrate, via k-means clustering of a set of amino acid sequences from the VIDA database, that the global kernel can be useful in bringing together otherwise very different protein families

Investigation of propylene carbonate synthesis regularities by the interaction of propylene glycol with carbamide

Objectives. Cyclic carbonates are important products of organic synthesis, which are widely used as solvents, catalysts, and reagents for the production of various compounds (in particular, urethane-containing polymers) by the non-isocyanate method. The process of carbamide alcoholysis with polybasic alcohols is a promising method for the synthesis of cyclic carbonates. The purpose of this study is to determine the reaction conditions for the interaction of propylene glycol with carbamide in the presence of zinc acetate as a catalyst.Methods. We conducted experiments to study the synthesis of propylene carbonate in a batch laboratory apparatus. Moreover, we analyzed the starting reagents and final products using gas–liquid chromatography.Results. We studied the synthesis of propylene carbonate by carbamide alcoholysis with propylene glycol in the presence of a catalyst (zinc acetate) by varying the following parameters: initial molar ratio of propylene glycol/carbamide = (0.5–5):1, synthesis temperature 130–190°С, reagent residence time in the reactor 0.5–4 h, and the catalyst amount in the reaction mixture 0–1.5 wt %.Conclusions. We determined the technological parameters of propylene carbonate synthesis in a batch reactor. Moreover, we showed that the process allowed the production of propylene carbonate with a sufficiently high yield of 80%—at the initial molar ratio of propylene glycol/ carbamide = 3:1, temperature 170°C, and residence time 2 h